Eric Horvitz: Publications by topic area

        View as single list       Selected publications

• Human-AI complementarity and collaboration
  
  
• Decisions, uncertainty, and intelligence
  
  
• Machine learning
  
  
• Dialog and situated interaction
  
  
• Interaction and Cognition
  
  
• Human computation and crowdsourcing
  
  
• Search, retrieval, social media and data
  
  
• Biomedical informatics
  
  
• Privacy
  
  
• Technology, Policy, and Society
  

Decisions, uncertainty, and intelligence

• H. Nori, Y. Lee, S. Zhang, D.Carignan, R. Edgar, N. Fusi, N. King, J. Larson, Y. Li, W. Liu, R. Luo, S. Mayer McKinney, R.O. Ness, H. Poon, T. Qin, N. Usuyama, C. White, and E. Horvitz, Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine, arXiv eprint: 2311.16452, November 27, 2023.
  
  
• H. Mozannar. G. Bansal, A. Fourney, E. Horvitz, When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming, AAAI 2024, February 2024.
  
  
• M. Poli, S. Massaroli, S. Ermon, B. Wilder, E. Horvitz, Ideal Abstractions for Decision-Focused Learning, AI and Statistics (AIStats), April 2023.
  
  
• H. Nori, N. King, S. Mayer McKinney, D. Carignan, E. Horvitz, Capabilities of GPT-4 on Medical Challenge Problems, arXiv preprint 2303.13375, March 20, 2023.
  
  S. Bubeck, V. Chandrasekaran, R. Eldan, J. Gehrke, E. Horvitz, E. Kamar, P. Lee, Y. Lee, Y. Li, S. Lundberg, H. Nori, H. Palangi, M. Ribeiro, Y. Zhang, Sparks of Artificial General Intelligence: Early experiments with GPT-4, arXiv preprint arXiv:2303.12712, March 22, 2023.
  
  
• S. Singla, B. Nushi, S. Shah, E. Kamar, E. Horvitz. Understanding Failures of Deep Networks via Robust Feature Extraction, CVPR 2021.
  
  
• M. Sap, A. Jafarpour, Y. Choi, N.A. Smith, J.W. Pennebaker, E. Horvitz. Imagined versus Remembered Stories: Quantifying Differences in Narrative Flows, Proceedings of the National Academy of Sciences (PNAS), 2022.
  
  
• B. Wilder, E. Horvitz, E. Kamar. Learning to Complement Humans, IJCAI 2020.
  
  
• M. Sap, E. Horvitz, Y. Choi, N.A. Smith, J.W. Pennebaker. Recollection versus Imagination: Exploring Human Memory and Cognition via Neural Language Models, ACL 2020.
  
  
• D.H. Lee, M. Yetisgen, L. Vanderwende, E. Horvitz. Predicting Severe Clinical Events by Learning about Life-Saving Actions and Outcomes using Distant Supervision, Journal of Biomedical Informatics 2020.
  
  
• U. Singer, K. Radinsky, E. Horvitz. On Biases of Attention in Scientific Discovery, Journal of Bioinformatics, December 2020. At J. Bioinformatics.
  
  
• A. Kolobov, Y. Peres, C. Lu, E. Horvitz. Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling, NeurIPS 2019.
  
  
• H. Aly, J. Krumm, G. Ranade, E. Horvitz. Computing Value of Spatiotemporal Information, CACM Research Highlight, CACM 2020.
  
  
• R. Selvaraju, P. Tendulkar, D. Parikh, E. Horvitz, M. Ribeiro, B. Nushi, E. Kamar. SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions, CVPR 2020.
  
  
• R. Ramakrishnan, E. Kamar, D. Dey, E. Horvitz, J. Shah. Blind Spot Detection for Safe Sim-to-Real Transfer, Journal of Artificial Intelligence Research 67 (2020) 191-234.
  
  
• X.Z. Tan, S. Andrist, D. Bohus, E. Horvitz. Now, Over Here: Leveraging Extended Attentional Capabilities in Human-Robot Interaction, HRI 2020.
  
  
• A. Modi, D. Dey, A. Agarwal, A. Swaminathan, B. Nushi, S. Andrist, E. Horvitz. Metareasoning in Modular Software Systems: On-the-Fly Configuration using Reinforcement Learning with Rich Contextual Representations, AAAI 2020.
  
  
• A. Kolobov, Y. Peres, C. Lu, E. Horvitz. Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling, NeurIPS 2019.
  
  
• H. Hu, J. Langford, R. Caruana, E. Horvitz, D. Dey Efficient Forward Architecture Search, NeurIPS 2019. Petridish code.
  
  
• A. Grover, J. Song, A. Agarwal, K. Tran, A. Kapoor, E. Horvitz, S. Ermon. Bias Correction of Learned Generative Models using Likelihood-free Importance Weighting, NeurIPS 2019.
  
  
• H. Aly, J. Krumm, G. Ranade, E. Horvitz. To Buy or Not to Buy: Computing Value of Spatiotemporal Information. ACM Transactions on Spatial Algorithms and Systems, 5(4) 2019.
  
  
• A. Kolobov, Y. Peres, E. Lubetzky, E. Horvitz. Optimal Freshness Crawl Under Politeness Constraints, SIGIR 2019.
  
  
• A. Modi, D. Dey, A. Agarwal, A. Swaminathan, B. Nushi, S. Andrist, E. Horvitz. Metareasoning in Modular Software Systems: On-the-Fly Configuration using Reinforcement Learning with Rich Contextual Representations, Workshop on Reinforcement Learning for Real Life, ICML 2019.
  
  
• A. Kolobov, Y. Peres, C. Lu, E. Horvitz. Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling, ICML 2019 Workshop on Reinforcement Learning for Real Life.
  
  
• R. Ramakrishnan, E. Kamar, B. Nushi, D. Dey, J. Shah, E. Horvitz. Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution, AAAI 2019.
  
  
• G. Bansal, B. Nushi, E. Kamar, et al. Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff, AAAI 2019.
  
  
• J. Krumm and E. Horvitz. Traffic Updates: Saying a Lot While Revealing a Little, AAAI 2019.
  
  
• R. West and E. Horvitz. Reverse-Engineering Satire, or "Paper on Computational Humor Accepted Despite Making Serious Advances", AAAI 2019.
  
  
• D. Bohus and E. Horvitz. Situated Interaction, in The Handbook of Multimodal-Multisensor Interfaces, Volume 3, ACM and Morgan & Claypool, July 2019, pp. 105-143. At ACM Digital Library
  
  
• G. Nordon, G. Koren, V. Shalev, E. Horvitz, K. Radinsky. Separating Wheat from Chaff: Joining Biomedical Knowledge and Patient Data for Repurposing Medications, IAAI 2019.
  
  
• Y. Azar, E. Horvitz, E. Lubetzky, Y. Peres, D. Shahaf. Tractable near-optimal policies for crawling, PNAS 2018. (pdf)
  
  
• H. Aly, J. Krumm, G. Ranade, E. Horvitz. On the Value of Spatiotemporal Information: Principles and Scenarios, ACM SIGSPATIAL 2018.
  
  
• R. Ramakrishnan, E. Kamar, D. Dey, J. Shah, E. Horvitz. Discovering Blind Spots in Reinforcement Learning, AAMAS 2018.
  
  
• B. Nushi, E. Kamar, E. Horvitz. Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure, HCOMP 2018.
  
  
• E.A. Platanios, H. Poon, T. M. Mitchell, E. Horvitz. Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach, NIPS 2017.
  
  
• A. Segal, Y. Gal, E. Kamar, E. Horvitz, G. Miller. Optimizing Interventions via Offline Policy Evaluation: Studies in Citizen Science, AAAI 2018.
  
  
• E. Horvitz. AI, People, and Society, Science 07 Jul 2017: Vol. 357, Issue 6346, pp. 7. DOI: 10.1126/science.aao2466
  
  
• H. Lakkaraju, E. Kamar, R. Caruana, E. Horvitz. Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration, AAAI 2017.
  
  
• B. Nushi, E. Kamar, E. Horvitz, D. Kossmann. On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems, AAAI 2017.
  
  
• C.H. Lin, A. Kolobov, E. Kamar, E. Horvitz. Metareasoning for Planning Under Uncertainty. In Proceedings of IJCAI 2015.
  
  
• S.J. Gershman, E.J. Horvitz, J.B. Tenenbaum. Computational Rationality: A Converging Paradigm for Intelligence in Brains, Minds, and Machines, 16 July 2015, Science 349. 273-278 (2015).
  
  
• C. Wu, E. Kamar, E. Horvitz. Clustering for Set Partitioning with a Case Study in Ridesharing, IEEE Intelligent Transportation Systems Conference (IEEE ITSC), November 2016. (Best paper award).
  
  
• J.C. Krumm and E. Horvitz. Risk-Aware Planning: Methods and Case Study for Safe Driving Routes, IAAI 2017.
  
  
• A. Singla, E. Horvitz, P. Kohli, R.W. White, A Krause. Information Gathering in Networks via Active Exploration. In Proceedings of IJCAI 2015.
  
  
• E. Kamar, A. Kapoor, E. Horvitz. Identifying and Accounting for Task-Dependent Bias in Crowdsourcing. In Proceedings of HCOMP 2015, Conference on Human Computation and Crowdsourcing, November 2015.
  
  
• E. Kamar and E. Horvitz. Planning for Crowdsourcing Hierarchical Tasks. In Proceedings of AAMAS 2015.
  
  
• J. Krumm and E. Horvitz. Eyewitness: Identifying Local Events via Space-Time Signals in Twitter Feeds. In Proceedings of SIGSpatial 2015.
  
  
• A. Singla, E. Horvitz, E. Kamar, R.W. White. Stochastic Privacy, AAAI, July 2014.
  
  
• M. Bayati, M. Braverman, M. Gillam, K.M. Mack, G. Ruiz, M.S. Smith, E. Horvitz. Data-Driven Decisions for Reducing Readmissions for Heart Failure: General Methodology and Case Study. PLOS One Medicine. October 2014.
  
  
• C.H. Lin, E. Kamar, E. Horvitz. Signals in the Silence: Models of Implicit Feedback in a Recommendation System for Crowdsourcing, AAAI, July 2014.
  
  
• N. Mishra, R. W. White, S. Ieong, E. Horvitz. Time-Critical Search, SIGIR 2014, July 2014.
  
  
• E. Kamar, A. Kapoor, and E. Horvitz. Lifelong Learning for Acquiring the Wisdom of the Crowd, IJCAI 2013, Beijing, China, August 2013.
  
  
• S. Jegelka, A. Kapoor, and E. Horvitz. An Interactive Approach to Solving Correspondence Problems, International Journal of Computer Vision, Special Issue on Active and Interactive Methods in Computer Vision, 2013.
  
  
• D. Dey, A. Kolobov, R. Caruana, E. Kamar, E. Horvitz, A. Kapoor. Gauss Meets Canadian Traveler: Shortest-Path Problems with Correlated Natural Dynamics, AAMAS 2014, Paris, France, May 2014.
  
  
• D. Bohus, C.W. Saw, E. Horvitz. Directions Robot: In-the-Wild Experiences and Lessons Learned, AAMAS 2014, Paris, France, May 2014.
  
  
• A. Kapoor, Z. Horvitz, S. Laube, E. Horvitz. Airplanes Aloft as a Sensor Network for Wind Forecasting, IPSN 2014, Berlin, Apri 2014. Access current U.S. windflows, inferred from thousands of planes in flight.
  
  
• S. Rosenthal, D. Bohus, E. Kamar, E. Horvitz. Look versus Leap: Computing Value of Information with High-Dimensional Streaming Evidence, IJCAI 2013, Beijing, China, August 2013.
  
  
• H. Zhang, E. Horvitz, D. Parkes. Automated Workflow Synthesis, AAAI 2013, Bellevue, Washington, July 2013.
  
  
• E. Kamar and E. Horvitz. Light at the End of the Tunnel: A Monte Carlo Approach to Computing Value of Information, AAMAS 2013, St. Paul, Minnesota, May 2013.
  
  
• A. Sadilek, J. Krumm, and E. Horvitz. Crowdphysics: Planned and Opportunistic Crowdsourcing for Physical Tasks, ICWSM 2013, Boston, MA, July 2013. Presentation at MIT Conference on Digital Experimentation (CODE 2014).
  
  
• E. Kamar, S. Hacker, E. Horvitz. Combining Human and Machine Intelligence in Large-scale Crowdsourcing, AAMAS 2012, Valencia, Spain, June 2012.
  
  
• X. Chen, P.N. Bennett, K. Collins-Thompson, E. Horvitz. Pairwise Ranking Aggregation in a Crowdsourced Setting, WSDM 2013, Rome, February 2013.
  
  
• E. Horvitz and J. Krumm. Some Help on the Way: Opportunistic Routing under Uncertainty, Ubicomp 2012, Pittsburgh, PA, September 2012.
  
  
• E. Horvitz. Reflections on Judea Pearl and his contributions (introductory comments at UAI special session), UAI 2012, Catalina, CA, August 2012 (photo after session).
  
  
• H. Zhang, E. Horvitz Y. Chen, and D. Parkes. Task Routing for Prediction Tasks, AAMAS 2012, Valencia, Spain, June 2012.
  
  
• E. Kamar and E. Horvitz. Incentives for Truthful Reporting in Crowdsourcing, AAMAS 2012, Valencia, Spain, June 2012.
  
  
• D. Shahaf and E. Horvitz. Generalized Task Markets for Human and Machine Computation, AAAI 2010, Atlanta, GA, July 2010.
  
  
• A. Krause and E. Horvitz. A Utility-theoretic Approach to Privacy in Online Services, Journal of Artificial Intelligence Research, 39 (2010) 633-662.
  
  
• A. Kapoor, S. Baker, S. Basu, E. Horvitz. Memory Constrained Face Recognition, CVPR 2012, Providence, Rhode Island, June, 2012.
  
  
• D. Bohus and E. Horvitz. Decisions about Turns in Multiparty Conversation: From Perception to Action, ICMI 2011: International Conference on Multimodal Interaction, Alicante, Spain, November, 2011.
  
  
• H. Zhang, E. Horvitz, Y. Chen, and D.C. Parkes, Task Routing for Prediction Tasks Workshop on Social Computing and User-Generated Content, EC 2011: 12th ACM Conference on Electronic Commerce , San Jose, June 2011.
  
  
• S. Seuken, D.Parkes, E. Horvitz, K. Jain, M. Czerwinski, and D. Tan, Market User Interface Design, Conference on Auctions, Market Mechanisms and their Applications(CHI), New York, NY, August 2011.
  
  
• E. Kamar and E. Horvitz, Jogger: Investigation of Principles of Context-Sensitive Reminding, Proceedings of International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Tapei, May 2011.
  
  
• E. Kamar and E. Horvitz. Collaboration and Shared Plans in the Open World: Studies of Ridesharing, IJCAI 2009, Pasadena, CA, July 2009.
  
  
• D. Shahaf and E. Horvitz. Investigations of Continual Computation, IJCAI 2009, Pasadena, CA, July 2009.
  
  
• A. Kapoor and E. Horvitz. Breaking Boundaries: Active Information Acquisition Across Learning and Diagnosis, NIPS 2009, Vancouver, BC, December 2009.
  
  
• E. Horvitz and W.B. Kristan, Toward a Computational Microscope for Neurobiology. In: T. Hey, S. Tansley, and K. Tolle, eds., The Fourth Paradigm: Data-Intensive Scientific Discovery, Redmond: Microsoft Research, 2009.
  
  
• E. Horvitz and T. Mitchell, From Data to Knowledge to Action: A Global Enabler for the 21st Century, Data Analytic Series, Computing Community Consortium, Computing Research Association (CRA), June 2010.
  
  
• A. Kapoor, N. Eagle, E. Horvitz. People, Quakes, and Communications: Inferences from Call Dynamics about a Seismic Event and its Influences on a Population. Proceedings of AAAI Symposium on Artificial Intelligence for Development, Stanford CA, March 2010.
  
  
• E. Kamar and E. Horvitz. Generating Shared Transportation Plans Under Varying Preferences: Ridesharing Models and Mechanisms, Microsoft Research Technical report, MSR-TR-2009-2011, April 2009.
  
  
• E. Horvitz. Artificial Intelligence in the Open World, AAAI Presidential Lecture, Chicago, IL, July 2008. (Presentation slides).
  
  
• E. Kamar, E. Horvitz, C. Meek. Mobile Opportunistic Commerce: Mechanisms, Architecture, and Application, Proceedings of AAMAS 2008, Estoril, Portugal, May 2008.
  
  
• A. Krause and E. Horvitz. A Utility-Theoretic Approach to Privacy and Personalization, AAAI-08: Twenty-Third Conference on Artificial Intelligence, Chicago, Illinois, July 2008.
  
  
• A. Kapoor, D. Tan, P. Shenoy, E. Horvitz. Complementary Computing for Visual Tasks: Meshing Computer Vision with Human Visual Processing, IEEE International Conference on Automatic Face and Gesture Recognition.
  
  
• A. Krause, E. Horvitz, A. Kansal, F. Zhao. Toward Community Sensing, Proceedings of IPSN 2008, International Conference on Information Processing in Sensor Networks, St. Louis, Missouri, April 2008.
  
  
• A. Krause and E. Horvitz. Privacy, Personalization, and the Web: A Utility-theoretic Approach, NIPS Workshop on Machine Learning for Web Search, Whistler, British Columbia, December 2007.
  
  
• A. Kapoor and E. Horvitz. Experience Sampling for Building Predictive User Models: A Comparative Study, Proceedings of CHI 2008, Florence, Italy, April 2008.
  
  
• A. Kapoor and E. Horvitz. On Discarding, Caching, and Recalling Samples in Active Learning, Proceedings of the Conference on Uncertainty and Artificial Intelligence 2007, AUAI Press, July 2007.
  
  
• A. Kapoor, E. Horvitz, and S. Basu. Selective Supervision: Guiding Supervised Learning with Decision-Theoretic Active Learning, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, January 2007.
  
  
• J. Krumm and E. Horvitz. Predestination: Where Do You Want to Go Today?, IEEE Computer, April 2007.
  
  
• J. Krumm, J. Letchner, and E. Horvitz. Map Matching with Travel Time Constraints, Society of Automotive Engineers (SAE), 2007 World Congress, April 2007.
  
  
• E. Horvitz. Reflections on Challenges and Promises of Mixed-Initiative Interaction, AAAI Magazine 28, Special Issue on Mixed-Initiative Assistants (2007).
  
  
• E. Horvitz and T. Paek. Complementary Computing: Policies for Transferring Callers from Dialog Systems to Human Receptionists. User Modeling and User Adapted Interaction 17 (2007).
  
  
• E. Horvitz and P. Koch. Mobile Opportunistic Planning: Methods and Models. Proceedings of the Eleventh Conference on User Modeling (UM 2007), June 2007, Corfu, Greece, pp. 238 247.
  
  
• J. Krumm and E Horvitz. Predestination: Inferring Destinations from Partial Trajectories, UbiComp 2006: Eighth International Conference on Ubiquitous Computing, September 2006.
  
  
• J. Letchner, J. Krumm, and E. Horvitz, Trip Router with Individualized Preferences: Incorporating Personalization into Route Planning, Eighteenth Conference on Innovative Applications of Artificial Intelligence, July 2006.
  
  
• E. Horvitz, Reflection: Expectations in 50 years, New Scientist, 50th Anniversary Edition, November 2006.
  
  
• E. Horvitz, From the Guest Editor: Special Issue on Graph-Based Representations, Decision Analysis 2(3):125 126, https://doi.org/10.1287/deca.1050.0051 September 2005.
  
  
• E. Horvitz, From the Guest Editor: New Contributions and Reflections on Graph-Based Representations for Decision Analysis, Decision Analysis 2(4):183-184, https://doi.org/10.1287/deca.1050.0061 December 2005.
  
  
• E. Horvitz, J. Apacible, M. Subramani. Balancing Awareness and Interruption: Investigation of Notification Deferral Policies. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• D. Achlioptas and E. Horvitz. Principles of Bounded Deferral for Balancing Information Awareness with Interruption. Microsoft Research Technical Report MSR-TR-2005-87, July 2005.
  
  
• N. Oliver and E. Horvitz. A Comparison of HMMs and Dynamic Bayesian Networks for Recognizing Office Activities. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• A. Youssef, J. Krumm, E. Miller, G. Cermak, E. Horvitz, Computing Location from Ambient FM Radio Signals, Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2005), March 2005.
  
  
• T. Paek and E. Horvitz. Optimizing Automated Call Routing by Integrating Spoken Dialog Models with Queuing Models, HLT 2004: Human Language Technology Conference, May 2004.
  
  
• Y. Ruan, H. Kautz, E. Horvitz, The Backdoor Key: A Path to Understanding Problem Hardness, Proceedings of the Nineteenth National Conference on Artificial Intelligence, AAAI 2004, San Jose, CA..
  
  
• J. Krumm and E. Horvitz, LOCADIO: Inferring Motion and Location from Wi-Fi Signal Strengths, Proceedings of the Mobiquitous 2004, Boston, MA..
  
  
• N. Oliver and E. Horvitz. Selective Perception Policies for Limiting Computation in Multimodal Systems: A Comparative Analysis, Proceedings of the Fifth ACM International Conference on Multimodal Interfaces, November 2003, Vancouver, BC, Canada.
  
  
• N. Oliver and E. Horvitz. Selective Perception Policies for Guiding Sensing and Computation in Multimodal Systems: A Comparative Analysis. Lectures Notes in Computer Science. Springer Verlag. January 2005.
  
  
• Y. Ruan, E. Horvitz, H. Kautz. Hardness-Aware Restart Policies. IJCAI-03 Workshop on Stochastic Search Algorithms, August 2003, Acapulco, Mexico.
  
  
• D. Azari, E. Horvitz, S. Dumais, E. Brill. A Decision Making Perspective on Web Question Answering, Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence, Acapulco, Mexico, August 2003.
  
  
• J. Krumm, G. Cermak, E. Horvitz. RightSPOT: A Novel Sense of Location for a Smart Personal Object, In Proceedings of Ubicomp 2003, Seattle, WA, pp. 36-43.
  
  
• U. Nodelman and E. Horvitz, Continuous Time Bayesian Networks for Inferring Users Presence and Activities with Extensions for Modeling and Evaluation, Microsoft Research Technical Report MSR-TR-2003-97, December 2003.
  
  
• Y. Ruan, E. Horvitz, H. Kautz, Restart Policies with Dependence among Runs: A Dynamic Programming Approach, In Proceedings of the Eighth International Conference on Principles and Practice of Constraint Programming, September 2002, Ithaca, New York.
  
  
• N. Oliver, E. Horvitz, and A. Garg. Layered Representations for Recognizing Office Activity, Proceedings of the Fourth IEEE International Conference on Multimodal Interaction (ICMI 2002), October 2002, Pittsburgh, PA, pp.3-8
  
  
• C.M. Kadie, D. Hovel, and E. Horvitz. MSBNx: A Component-Centric Toolkit for Modeling and Inference with Bayesian Networks. Microsoft Research Technical Report MSR-TR-2001-67, July 2001.
  
  
• H. Kautz, E. Horvitz, Y. Ruan, C. Gomes, B. Selman. Dynamic Restart Policies. Proceedings of the Eighteenth National Conference on Artificial Intelligence, Edmonton, Alberta, July 2002. AAAI Press.
  
  
• E. Horvitz. Principles and Applications of Continual Computation, Artificial Intelligence Journal, 126:159-196, Elsevier Science, February 2001.
  
  
• E. Horvitz and S. Zilberstein, Computational Tradeoffs Under Bounded Resources, Artificial Intelligence Journal, 126:1-4, Elsevier Science, February 2001.
  
  
• E. Horvitz, Y. Ruan, C. Gomes, H. Kautz, B. Selman, D. M. Chickering. A Bayesian Approach to Tackling Hard Computational Problems. Proceedings of the Seventeenth Conference on Uncertainty and Artificial Intelligence, July 2001, pp. 235-244. Morgan Kaufmann Publishers: San Francisco.
  
  
• E. Horvitz. Principles of Mixed-Initiative User Interfaces. Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, May 1999. more info, Lookout video, Lookout as star of a TV commercial (1999)
  
  
• E. Horvitz, A. Jacobs, D. Hovel. Attention-Sensitive Alerting, Proceedings of UAI '99, Conference on Uncertainty and Artificial Intelligence, July 1999, Morgan Kaufmann Publishers: San Francisco. pp. 305-313. pdf, video
  
  
• S. Srinivas and E. Horvitz. Exploiting System Hierarchy to Compute Repair Plans in Probabilistic Model-Based Diagnosis. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, August 1995.
  
  
• K. L. Poh and E. Horvitz. A Graph-Theoretic Analysis of Information Value. Proceedings of the Twelfth Conference on Uncertainty in Artificial Intelligence, August 1996.
  
  
• E. Horvitz. Models of Continual Computation. Proceedings of the Fourteenth National Conference on Artificial Intelligence, July 1997.
  
  
• E. Horvitz and A. Seiver. Time-Critical Action: Representations and Application. Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, August 1997.
  
  
• E. Horvitz. Continual Computation Policies for Utility-Directed Prefetching. Proceedings of the Seventh ACM Conference on Information and Knowledge Management, November 1998, pp. 175-184.
  
  
• E. Horvitz. Thinking Ahead: Continual Computation Policies for Allocating Offline and Real-Time Resources. Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI '99, July 1999, Morgan Kaufmann Publishers: San Francisco, pp. 1280-1286.
  
  
• D. Heckerman, E. Horvitz, and B. Middleton, An approximate nonmyopic computation for value of information, IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 15 (1993), 3:292-298.
  
  
• E. Horvitz and J. Lengyel. Perception, Attention, and Resources: A Decision-Theoretic Approach to Graphics Rendering. Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, August 1997, Morgan Kaufman: San Francisco, pp. 238-249.
  
  
• E. Horvitz and Jed Lengyel. Flexible Rendering of 3D Graphics Under Varying Resources: Issues and Directions, Symposium on Flexible Computation, M.I.T., Cambridge MA, AAAI: Menlo Park, CA, November 1996, pages 81-88.
  
  
• P. Dagum, P., A. Galper, E. Horvitz, A. Seiver, Uncertain reasoning and forecasting, International Journal of Forecasting 11(1):73-87, March 1995.
  
  
• P. Dagum and E. J. Horvitz. Reformulating Inference Problems through Selective Conditioning, Proceedings of 1992 Conference on Uncertainty in Artificial Intelligence, Stanford, CA, July 1992 pdf).
  
  
• E. Horvitz, J. Breese, D. Heckerman, D. Hovel, and K. Rommelse. The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July 1998, Morgan Kaufmann: San Francisco, pp. 256-265.   Video   More on Lumiere.
  
  
• B. Selman, R. Brooks, T. Dean, E. Horvitz, T. Mitchell, N. Nilsson. Challenge Problems for Artificial Intelligence. Proceedings of AAAI-96, Thirteenth National Conference on Artificial Intelligence, Portland, Oregon, August 1996. AAAI Press, Menlo Park, California, pp. 1340-1345 (audio available).
  
  
• E. Horvitz and A. Klein. Studies of Theorem Proving under Limited Resources. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, August 1995.
  
  
• L. Burnell and E. Horvitz, Structure and Chance: Melding Logic and Probability for Software Debugging. Communications of the ACM, 38:3, March 1995, pp. 31-41, 1995.
  
  
• E. Horvitz and M Barry. Display of Information for Time-Critical Decision Making. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, August 1995 (pdf).
  
  
• A. Klein and E. Horvitz, Partial Proofs and Probability, Proceedings of DX-94: Fifth International Workshop on Principles of Diagnosis, New Paltz, NY, October 1994.
  
  
• K.L. Poh, M.R. Fehling, and E.J. Horvitz, Dynamic Construction and Refinement of Utility-Based Categorization Models, IEEE Transaction on Systems, Man, and Cybernetics, 24(11), 1653-1663, November 1994.
  
  
• E. Horvitz and A. Klein, Utility-Based Abstraction and Categorization. Proceedings of Ninth Conference on Uncertainty in Artificial Intelligence, Washington DC, July 1993. Morgan Kaufmann: San Francisco, pp. 128-135 (pdf).
  
  
• P. Dagum and E. Horvitz. A Bayesian Analysis of Simulation Algorithms for Inference in Belief Networks. Networks, 23:499-516, 1993.
  
  
• K.L. Poh and E. Horvitz. Reasoning about the Value of Decision Model Refinement: Methods and Application. Proceedings of Ninth Conference on Uncertainty in Artificial Intelligence, Washington DC, July 1993, Morgan Kaufmann: San Francisco, pp. 174-182.
  
  
• J. Breese, E. Horvitz, M. Peot, R. Gay, and G. Quentin, Automated Decision-Analytic Diagnosis of Thermal Performance in Gas Turbines, Proceedings of the International Gas Turbine and Aeroengine Congress and Exposition, Cologne, Germany, 1992.
  
  
• P. Dagum, A. Galper, and E. J. Horvitz. Dynamic Network Models for Forecasting, Proceedings of 1992 Conference on Uncertainty in Artificial Intelligence, Stanford, CA, July 1992 (pdf).
  
  
• E. Horvitz and G. Rutledge. Time-Dependent Utility and Action Under Uncertainty. Uncertainty in Artificial Intelligence, Los Angeles, pp. 151-158. Morgan Kaufman, 1991 (pdf).
  
  
• E. Horvitz. Decision Analysis in Design: Identifying Valuable Configurations with Expected Utility and Search. Technical Memorandum 104, Rockwell International Science Center, Palo Alto, CA, February 1993.
  
  
• E. Horvitz, D. Heckerman, K. Ng, B. Nathwani, Heuristic Abstraction in the Decision-Theoretic Pathfinder System, Symposium on Computer Applications in Medical Care, Washington DC, IEEE Press: Silver Springs, MD, November 1989.
  
  
• J.S. Breese and E.J. Horvitz. Ideal Reformulation of Belief Networks , Proceedings of Sixth Conference on Uncertainty in Artificial Intelligence, Cambridge, MA, Association for Uncertainty in Artificial Intelligence, Mountain View, CA. July 1990, pp. 64-72 (pdf).
  
  
• D. E. Heckerman, E. J. Horvitz, and B. N. Nathwani. Toward Normative Expert Systems: Part I The Pathfinder Project. Methods of Information in Medicine, 31:90-105, 1992 (pdf).
  
  
• E. Horvitz. Computation and Action under Bounded Resources. PhD Dissertation, Stanford University, 1990 (pdf).
  
  
• D. Heckerman and E. Horvitz. Problem Formulation as the Reduction of a Decision Problem. Proceedings of the Conference on Uncertainty in Artificial Intelligence, Cambridge, MA July 1990, Association for Uncertainty and Artificial Intelligence, pp. 82-89.
  
  
• E.J. Horvitz, H.J. Suermondt, G.F. Cooper. Bounded conditioning: Flexible inference for decisions under scarce resources. In: Proceedings of Conference on Uncertainty in Artificial Intelligence, Windsor, ON. August 1989, pp. 182-193. Association for Uncertainty in Artificial Intelligence, Mountain View, CA.
  
  
• E. Horvitz. Research on Principles of Bounded Rationality. Proceedings of AAAI Symposium on Artificial Intelligence in Medicine, Stanford CA, March 1990.
  
  
• E.J. Horvitz, J.S. Breese, M. Henrion, Decision Theory in Expert Systems and Artificial Intelligence, Journal of Approximate Reasoning, Special Issue on Uncertainty in Artificial Intelligence, 2:247-302, 1988.
  
  
• E.J. Horvitz and J.S. Breese, Ideal Partition of Resources for Metareasoning. Stanford University Computer Science Department Technical Report KSL-90-26, February 1990.
  
  
• E. Horvitz, Some Fundamental Problems and Opportunities From the Standpoint of Rational Agency. Stanford University Computer Science Department Technical Report KSL-89-30, 1989 (pdf).
  
  
• E.J. Horvitz, Rational Metareasoning and Compilation for Optimizing Decisions Under Bounded Resources. Proceedings of Computational Intelligence '89, Milan, Italy, September 1989. Association for Computing Machinery.
  
  
• E.J. Horvitz, G.F. Cooper, D.E. Heckerman, Reflection and action under scarce resources: Theoretical principles and empirical study. Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI. August 1989, pp. 1121-1127. International Joint Conference on Artificial Intelligence.
  
  
• D. Heckerman, J.S. Breese, E. Horvitz, The Compilation of Decision Models, Proceedings of the Conference on Uncertainty in Artificial Intelligence, Association for Uncertainty in Artificial Intelligence, July 1989, pages 162-173.
  
  
• E.J. Horvitz, Reasoning under varying and uncertain resource constraints. Proceedings of the Seventh National Conference on Artificial Intelligence, Minneapolis, MN. August 1988. pp, 111-116. Morgan Kaufmann, San Mateo, CA.
  
  
• G. Cooper, E. Horvitz, R. Curry, Conceptual Design of Goal Understanding Systems: Investigation of Temporal Reasoning Under Uncertainty, Technical Memorandum NAS2-12381, NASA-Ames Research Center, Mountain View, CA, Feburary 1988.
  
  
• G.F. Cooper, E.J. Horvitz, D.E. Heckerman, A Method for Temporal Probabilistic Reasoning, Technical Report 88-30. Knowledge Systems Laboratory, Stanford University, July 1988.
  
  
• E.J. Horvitz, Problem-Solving Design: Reasoning about Computational Value, Tradeoffs, and Resources. Proceedings of the NASA Artificial Intelligence Forum, Palo Alto, CA, October 1987, pp. 26-43. National Aeronautics And Space Administration: Mountain View, CA.
  
  
• E. Horvitz, D.E. Heckerman, and C.P. Langlotz. A Framework for Comparing Alternative Formalisms for Plausible Reasoning. Proceeedings of AAAI-86, National Conference on Artificial Intelligence, Morgan Kaufmann, Philadelphia, Morgan Kaufmann, July 1986, pp. 210-214 (pdf).
  
  
• D.E. Heckerman and E.J. Horvitz. The Myth of Modularity in Rule-Based Systems for Reasoning with Uncertainty, Proceedings of UAI-86, Conference on Uncertainty in Artificial Intelligence, Philadelphia, July 1986 (pdf).
  
  
• D.E. Heckerman and E.J. Horvitz, On the Expressiveness of Rule-Based Systems for Reasoning with Uncertainty, Proceedings of AAAI-87, National Conference on Artificial Intelligence, Seattle, WA, Morgan Kaufmann, July 1987, pp. 121-126.
  
  
• E. Horvitz, Reasoning about Beliefs and Actions under Computational Resource Constraints, In L. Kanal, et al. ed., Uncertainty in Artificial Intelligence 3, Elsevier, 1989, pp. 301-324.
  
  
• E. Horvitz, Reasoning about Beliefs and Actions under Computational Resource Constraints, Proceedings of the Third Conference on Uncertainty in Artificial Intelligence, Seattle, Washington. July 1987. Association for Uncertainty and Artificial Intelligence. Conference on Uncertainty and Artificial Intelligence (UAI-87), July 1987, pp. 429-444. An extended version of this conference article published as chapter in: L. Kanal, et al. ed., Uncertainty in Artificial Intelligence 3,Elsevier, 1989, pp. 301-324.
  
  
• E.J. Horvitz, Toward a Science of Expert Systems, In: Proceedings of the 18th Symposium on the Interface of Statistics and Computer Science, Fort Collins, Colorado, March 1986, Thomas J. Boardman, Editor, American Statistical Association: Washington, D.C., pp. 45-52 (pdf).
  
  
• E. Horvitz, D. Heckerman, B. Nathwani, L.M. Fagan, The use of a heuristic problem-solving hierarchy to facilitate the explanation of hypothesis-directed reasoning, October 1986, In: Proceedings of Medinfo, Washington, DC, North Holland: New York, pp. 27-31.
  
  
• E.J. Horvitz and D.E. Heckerman, Modular Belief Updates and Confusion about Measures of Certainty in Artificial Intelligence Research, Proceedings of UAI-85, AAAI Workshop on Uncertainty in Artificial Intelligence, Los Angeles, CA July 1985.
  
  
• E.J. Horvitz and D.E. Heckerman, The Inconsistent Use of Measures of Certainty in Artificial Intelligence Research, Uncertainty in Artificial Intelligence I, Elsevier, 1986.
  
  
• E.J. Horvitz, D.E. Heckerman, B.N. Nathwani, L.M. Fagan, Diagnostic Strategies in the Hypothesis-Directed Pathfinder System, In: Proceedings of the First Conference on Artificial Intelligence Applications, Denver, Colorado, December 1984. IEEE Computer Society, Computer Society Press, pp. 630-636 (pdf).
  
  

Machine Learning

• H. Nori, Y. Lee, S. Zhang, D.Carignan, R. Edgar, N. Fusi, N. King, J. Larson, Y. Li, W. Liu, R. Luo, S. Mayer McKinney, R.O. Ness, H. Poon, T. Qin, N. Usuyama, C. White, and E. Horvitz, Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine, arXiv eprint: 2311.16452, November 27, 2023.
  
  
• M. Poli, S. Massaroli, S. Ermon, B. Wilder, E. Horvitz, Ideal Abstractions for Decision-Focused Learning, AI and Statistics (AIStats), April 2023.
  
  
• H. Nori, N. King, S. Mayer McKinney, D. Carignan, E. Horvitz, Capabilities of GPT-4 on Medical Challenge Problems, arXiv preprint 2303.13375, March 20, 2023.
  
  S. Bubeck, V. Chandrasekaran, R. Eldan, J. Gehrke, E. Horvitz, E. Kamar, P. Lee, Y. Lee, Y. Li, S. Lundberg, H. Nori, H. Palangi, M. Ribeiro, Y. Zhang, Sparks of Artificial General Intelligence: Early experiments with GPT-4, arXiv preprint arXiv:2303.12712, March 22, 2023.
  
  
• D. Bohus, S. Andrist, A. Feniello, N. Saw, E. Horvitz, Continual Learning about Objects in the Wild: An Interactive Approach, International Conference on Multimodal Interaction (ICMI), November 2022.
  
  
• E. Horvitz, On the Horizon: Interactive and Compositional Deepfakes, International Conference on Multimodal Interaction (ICMI), November 2022. video
  
  
• B. Wilder, E. Horvitz, E. Kamar. Learning to Complement Humans, IJCAI 2020.
  
  
• S. Singla, B. Nushi, S. Shah, E. Kamar, E. Horvitz. Understanding Failures of Deep Networks via Robust Feature Extraction, CVPR 2021.
  
  
• M. Sap, E. Horvitz, Y. Choi, N.A. Smith, J.W. Pennebaker. Recollection versus Imagination: Exploring Human Memory and Cognition via Neural Language Models, ACL 2020.
  
  
• U. Singer, K. Radinsky, E. Horvitz. On Biases of Attention in Scientific Discovery, Journal of Bioinformatics, December 2020. At J. Bioinformatics.
  
  
• G. Bansal, B. Nushi, E. Kamar, et al. Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork, AAAI 2021.
  
  
• D.H. Lee, M. Yetisgen, L. Vanderwende, E. Horvitz. Predicting Severe Clinical Events by Learning about Life-Saving Actions and Outcomes using Distant Supervision, Journal of Biomedical Informatics 2020.
  
  M. Srivastava, B. Nushi, E. Kamar, S. Shah, E. Horvitz. Backward Compatibility in Machine Learning Systems, Knowledge Discovery and Data Mining (KDD), August 2020.
  
  
• H. Hu, J. Langford, R. Caruana, E. Horvitz, D. Dey Efficient Forward Architecture Search, NeurIPS 2019. Petridish code.
  
  
• R. Selvaraju, P. Tendulkar, D. Parikh, E. Horvitz, M. Ribeiro, B. Nushi, E. Kamar. SQuINTing at VQA Models: Interrogating VQA Models with Sub-Questions, CVPR 2020.
  
  
• R. Ramakrishnan, E. Kamar, D. Dey, E. Horvitz, J. Shah. Blind Spot Detection for Safe Sim-to-Real Transfer, Journal of Artificial Intelligence Research 67 (2020) 191-234.
  
  
• A. Modi, D. Dey, A. Agarwal, A. Swaminathan, B. Nushi, S. Andrist, E. Horvitz. Metareasoning in Modular Software Systems: On-the-Fly Configuration using Reinforcement Learning with Rich Contextual Representations, AAAI 2020.
  
  
• A. Kolobov, Y. Peres, C. Lu, E. Horvitz. Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling, NeurIPS 2019.
  
  
• A. Grover, J. Song, A. Agarwal, K. Tran, A. Kapoor, E. Horvitz, S. Ermon. Bias Correction of Learned Generative Models using Likelihood-free Importance Weighting, NeurIPS 2019.
  
  
• G. Bansal, B. Nushi, E. Kamar, et al. Beyond Accuracy: On the Role of Mental Models in Human-AI Teams, HCOMP 2019.
  
  
• J. Krumm and E. Horvitz. Traffic Updates: Saying a Lot While Revealing a Little, AAAI 2019.
  
  
• R. Ramakrishnan, E. Kamar, B. Nushi, D. Dey, J. Shah, E. Horvitz. Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution, AAAI 2019.
  
  
• J. Krumm and E. Horvitz. Traffic Updates: Saying a Lot While Revealing a Little, AAAI 2019.
  
  
• A. Kolobov, Y. Peres, E. Lubetzky, E. Horvitz. Optimal Freshness Crawl Under Politeness Constraints, SIGIR 2019.
  
  
• A. Kolobov, Y. Peres, C. Lu, E. Horvitz. Staying up to Date with Online Content Changes Using Reinforcement Learning for Scheduling, ICML 2019 Workshop on Reinforcement Learning for Real Life.
  
  
• R. Ramakrishnan, E. Kamar, D. Dey, J. Shah, E. Horvitz. Discovering Blind Spots in Reinforcement Learning, AAMAS 2018.
  
  
• B. Nushi, E. Kamar, E. Horvitz. Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure, HCOMP 2018.
  
  
• Y. Azar, E. Horvitz, E. Lubetzky, Y. Peres, D. Shahaf. Tractable near-optimal policies for crawling, PNAS 2018. (pdf)
  
  
• E. Horvitz. AI, People, and Society, Science 07 Jul 2017: Vol. 357, Issue 6346, pp. 7. DOI: 10.1126/science.aao2466
  
  
• E.A. Platanios, H. Poon, T. M. Mitchell, E. Horvitz. Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach, NIPS 2017.
  
  
• A. Segal, Y. Gal, E. Kamar, E. Horvitz, G. Miller. Optimizing Interventions via Offline Policy Evaluation: Studies in Citizen Science, AAAI 2018.
  
  
• D.H. Lee, M. Yetisgen, L. Vanderwende, E. Horvitz. Predicting Severe Clinical Events by Learning about Life-Saving Actions and Outcomes using Distant Supervision, Journal of Biomedical Informatics 2020.
  
  
• H. Lakkaraju, E. Kamar, R. Caruana, E. Horvitz. Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration, AAAI 2017.
  
  
• B. Nushi, E. Kamar, E. Horvitz, D. Kossmann. On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems, AAAI 2017.
  
  
• J.C. Krumm and E. Horvitz. Risk-Aware Planning: Methods and Case Study for Safe Driving Routes, IAAI 2017.
  
  
• A. Howard, C. Zhang, E. Horvitz. Addressing Bias in Machine Learning Algorithms: A Pilot Study on Emotion Recognition for Intelligent Systems. IEEE Workshop on Advanced Robotics and its Social Impacts, Austin, USA on March 8-10, 2017, Austin, TX. DOI: 10.1109/ARSO.2017.8025197
  
  
• J. Wiens, J. Guttag, and E. Horvitz. Patient Risk Stratification with Time-Varying Parameters: A Multitask Learning Approach. Journal of Machine Learning Research (JMLR), April 2016.
  
  
• D. Woodard, G. Nogin, P. Koch, D. Racz, M. Goldszmidt, E. Horvitz. Predicting Travel Time Reliability using Mobile Phone GPS Data, Transportation Research Part C, 70 (2017) pp. 30-44.
  
  
• R. W. White and E. Horvitz. Early Signs of Lung Carcinoma in Web Search Logs: Findings and Implications, JAMA Oncology, November 2016.
  
  
• E. Fast and E. Horvitz. Identifying Dogmatism in Social Media: Signals and Models, Empirical Methods in Natural Language Processing 2016 (EMNLP), Austin TX, November 2016.
  
  
• J.C. Krumm and E. Horvitz. Risk-Aware Planning: Methods and Case Study for Safe Driving Routes, IAAI 2016, AAAI January 2017.
  
  
• E. P. Frady, A. Kapoor, E. Horvitz, W.B. Kristan. Scalable Semisupervised Functional Neurocartography Reveals Canonical Neurons in Behavioral Networks, Neural Computation, June 2016. doi:10.1162/NECO_a_00852.
  
  
• D. Shahaf, E. Horvitz, R. Mankoff. Inside Jokes: Identifying Humorous Cartoon Captions. In Proceedings of KDD 2015.
  
  
• A. Grover, A. Kapoor, E. Horvitz. A Deep Hybrid Model for Weather Forecasting. In Proceedings of KDD 2015.
  
  
• E. Kamar, A. Kapoor, E. Horvitz. Identifying and Accounting for Task-Dependent Bias in Crowdsourcing. In Proceedings of HCOMP 2015, Conference on Human Computation and Crowdsourcing, November 2015.
  
  
• M. Bayati, M. Braverman, M. Gillam, K.M. Mack, G. Ruiz, M.S. Smith, E. Horvitz. Data-Driven Decisions for Reducing Readmissions for Heart Failure: General Methodology and Case Study. PLOS One Medicine. October 2014.
  
  
• J. Wiens, Wayne N. Campbell, Ella S. Franklin, J. Guttag, E. Horvitz. Learning Data-Driven Patient Risk Stratification Models for Clostridium difficile. Open Forum Infectious Diseases Advance Access, June 2014.
  
  
• J. Wiens, J. Guttag, and E. Horvitz. A Study in Transfer Learning: Leveraging Data from Multiple Hospitals to Enhance Hospital-Specific Predictions, Journal of the American Medical Informatics Association: 0:1 8, January 2014.
  
  
• E. Kamar, A. Kapoor, and E. Horvitz. Lifelong Learning for Acquiring the Wisdom of the Crowd, IJCAI 2013, Beijing, China, August 2013.
  
  
• J. Wiens, J. Guttag, E. Horvitz. Patient Risk Stratification for Hospital-Associated C. Diff as a Time-Series Classification Task, NIPS 2012, Lake Tahole, CA, December 2012.
  
  
• K. Radinsky and E. Horvitz. Mining the Web to Predict Future Events, WSDM 2013, Rome, February 2013.
  
  
• H. Zhang, E. Horvitz, D. Parkes. Automated Workflow Synthesis, AAAI 2013, Bellevue, Washington, July 2013.
  
  
• M. De Choudhury, S. Counts, E. Horvitz. Predicting Postpartum Changes in Emotion and Behavior via Social Media, CHI 2013, April 2013, Paris, France.
  
  
• X. Chen, P.N. Bennett, K. Collins-Thompson, E. Horvitz. Pairwise Ranking Aggregation in a Crowdsourced Setting, WSDM 2013, Rome, February 2013.
  
  
• K. Radinsky and E. Horvitz. Mining the Web to Predict Future Events, WSDM 2013, Rome, February 2013.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Learning to Learn: Algorithmic Inspirations from Human Problem Solving, AAAI 2012, Toronto, July 2012.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Performance and Preferences: Interactive Refinement of Machine Learning Procedures, AAAI 2012, Toronto, July 2012.
  
  
• K. Radinsky and E. Horvitz. Mining the Web to Predict Future Events, WSDM 2013, Rome, February 2013.
  
  
• K. Radinsky, K. Svore, S. Dumais, J. Teevan, A. Bocharov, E. Horvitz. Modeling and Predicting Behavioral Dynamics on the Web, WWW 2012, Lyon, France, April 2012.
  
  
• J. Wiens, J. Guttag, E. Horvitz. Learning Evolving Patient Risk Processes for C. Diff Colonization, Machine Learning for Clinical Data Analysis, ICML 2012, Edinburgh, Scotland, June 2012.
  
  
• A. Kapoor and E. Horvitz. Breaking Boundaries: Active Information Acquisition Across Learning and Diagnosis, NIPS 2009, Vancouver, BC, December 2009.
  
  
• E. Horvitz and T. Mitchell, From Data to Knowledge to Action: A Global Enabler for the 21st Century, Data Analytic Series, Computing Community Consortium, Computing Research Association (CRA), June 2010.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Interactive Optimization for Steering Classification, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Atlanta, GA, April 2010.
  
  
• A. Kapoor, N. Eagle, E. Horvitz. People, Quakes, and Communications: Inferences from Call Dynamics about a Seismic Event and its Influences on a Population. Proceedings of AAAI Symposium on Artificial Intelligence for Development, Stanford CA, March 2010.
  
  
• D. Downey, S. Dumais, D. Leibling, E. Horvitz. Understanding the Relationship between Searchers Queries and Information Goals, Proceedings of CIKM 2008, 17th Conference on Information and Knowledge Management, Napa, California, October 2008.
  
  
• A. Kapoor, D. Tan, P. Shenoy, E. Horvitz. Complementary Computing for Visual Tasks: Meshing Computer Vision with Human Visual Processing, IEEE International Conference on Automatic Face and Gesture Recognition.
  
  
• A. Krause, E. Horvitz, A. Kansal, F. Zhao. Toward Community Sensing, Proceedings of IPSN 2008, International Conference on Information Processing in Sensor Networks, St. Louis, Missouri, April 2008.
  
  
• A. Kapoor and E. Horvitz. Experience Sampling for Building Predictive User Models: A Comparative Study, Proceedings of CHI 2008, Florence, Italy, April 2008.
  
  
• J. Leskovec, S. Dumais, E. Horvitz. Web Projections: Learning from Contextual Subgraphs of the Web, Proceedings of World Wide Web 2007, Banff, Canada, May 2007.
  
  
• A. Kapoor and E. Horvitz. On Discarding, Caching, and Recalling Samples in Active Learning, Proceedings of the Conference on Uncertainty and Artificial Intelligence 2007, AUAI Press, July 2007.
  
  
• A. Kapoor, E. Horvitz, and S. Basu. Selective Supervision: Guiding Supervised Learning with Decision-Theoretic Active Learning, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, January 2007.
  
  
• D. Downey, S. Dumais, and E. Horvitz. Models of Searching and Browsing: Languages, Studies, and Applications, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, January 2007.
  
  
• E. Horvitz and T. Paek. Complementary Computing: Policies for Transferring Callers from Dialog Systems to Human Receptionists. User Modeling and User Adapted Interaction 17 (2007).
  
  
• E Horvitz. Machine Learning, Reasoning, and Intelligence in Daily Life: Directions and Challenges (Invited talk), Proceedings of Artificial Intelligence Techniques for Ambient Intelligence, Hyderabad, India, January 2007.
  
  
• A. Kapoor and E. Horvitz. Principles of Lifelong Learning for Predictive User Modeling. Proceedings of the Eleventh Conference on User Modeling (UM 2005), June 2007, Corfu, Greece.
  
  
• F. Bach, D. Heckerman, E. Horvitz. Considering Cost Asymmetry in Learning Classifiers. Journal of Machine Learning Research, 7 (2006) 1713 1741.
  
  E. Horvitz, J. Apacible, R. Sarin, and L. Liao. Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service, Proceedings of the Conference on Uncertainty and Artificial Intelligence 2005,, AUAI Press, July 2005.
  
  
• F. Bach, D. Heckerman, and E. Horvitz. On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers. Proceedings of Artificial Intelligence and Statistics 2005, January, 2005.
  
  
• E. Horvitz, J. Apacible, and P. Koch. BusyBody: Creating and Fielding Personalized Models of the Cost of Interruption, Proceedings of CSCW, Conference on Computer Supported Cooperative Work, ACM Press, November 2004.
  
  
• E. Horvitz and J. Apacible. Learning and Reasoning about Interruption. Proceedings of the Fifth ACM International Conference on Multimodal Interfaces, November 2003, Vancouver, BC, Canada.
  
  
• N. Oliver and E. Horvitz. A Comparison of HMMs and Dynamic Bayesian Networks for Recognizing Office Activities. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• E. Horvitz, P. Koch, R. Sarin, J. Apacible, M. Subramani. Bayesphone: Context-Sensitive Policies for Inquiry and Action in Mobile Devices. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• A. Youssef, J. Krumm, E. Miller, G. Cermak, E. Horvitz, Computing Location from Ambient FM Radio Signals, Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2005), March 2005.
  
  
• T. Paek and E. Horvitz. Optimizing Automated Call Routing by Integrating Spoken Dialog Models with Queuing Models, HLT 2004: Human Language Technology Conference, May 2004.
  
  
• D. Azari, E. Horvitz, S. Dumais, E. Brill. Actions, Answers, and Uncertainty: A Decision Making Perspective on Web-Based Question Asking , Information Processing and Management, 40(5), 2004, pp. 849-868.
  
  
• E. Horvitz, S. Dumais, P. Koch. Learning Predictive Models of Memory Landmarks, CogSci 2004: 26th Annual Meeting of the Cognitive Science Society, Chicago, August 2004.
  
  
• E. Horvitz, S. Dumais, P. Koch. Models of Memorability: Learning, Experiments, and Applications, Microsoft Research Technical Report, October 2003.
  
  
• J. Krumm and E. Horvitz, LOCADIO: Inferring Motion and Location from Wi-Fi Signal Strengths, Proceedings of the Mobiquitous 2004, Boston, MA..
  
  
• N. Oliver, A. Garg, and Eric Horvitz. Layered Representations for Learning and Inferring Office Activity from Multiple Sensory Channels, Computer Vision and Image Understanding (CVIU), 96(2004), pp. 163-180.
  
  
• N. Oliver and E. Horvitz. Selective Perception Policies for Guiding Sensing and Computation in Multimodal Systems: A Comparative Analysis. Lectures Notes in Computer Science. Springer Verlag. January 2005.
  
  
• Y. Ruan, E. Horvitz, H. Kautz. Hardness-Aware Restart Policies. IJCAI-03 Workshop on Stochastic Search Algorithms, August 2003, Acapulco, Mexico.
  
  
• P. N. Bennett, S. T. Dumais, E. Horvitz. Inductive Transfer for Text Classification using Generalized Reliability Indicators, Proceedings of the ICML-2003 Workshop on The Continuum from Labeled to Unlabeled Data, Washington DC, August 2003.
  
  
• P. N. Bennett, S. T. Dumais, and E. Horvitz. The Combination of Text Classifiers using Reliability Indicators. Information Retrieval.
  
  
• J. Krumm, G. Cermak, E. Horvitz. RightSPOT: A Novel Sense of Location for a Smart Personal Object, In Proceedings of Ubicomp 2003, Seattle, WA, pp. 36-43.
  
  
• U. Nodelman and E. Horvitz, Continuous Time Bayesian Networks for Inferring Users Presence and Activities with Extensions for Modeling and Evaluation, Microsoft Research Technical Report MSR-TR-2003-97, December 2003.
  
  
• D. Azari, E. Horvitz, S. Dumais, E. Brill. A Decision Making Perspective on Web Question Answering, Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence, Acapulco, Mexico, August 2003.
  
  
• Y. Ruan, E. Horvitz, H. Kautz, Restart Policies with Dependence among Runs: A Dynamic Programming Approach, In Proceedings of the Eighth International Conference on Principles and Practice of Constraint Programming, September 2002, Ithaca, New York.
  
  
• N. Oliver, E. Horvitz, and A. Garg. Layered Representations for Recognizing Office Activity, Proceedings of the Fourth IEEE International Conference on Multimodal Interaction (ICMI 2002), October 2002, Pittsburgh, PA, pp.3-8
  
  
• P. N. Bennett, S. T. Dumais, and E. Horvitz. Probabilistic Combination of Text Classifiers Using Reliability Indicators: Models and Results. In: Proceedings of 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Tampere, Finland, August 2002.
  
  
• E. Horvitz, P. Koch, C.M. Kadie, and A. Jacobs. Coordinate: Probabilistic Forecasting of Presence and Availability.Proceedings of UAI '02, Proceedings of the Eighteenth Conference on Uncertainty and Artificial Intelligence, Edmonton, Canada, July 2002, pp. 224-233.
  
  
• C. R. Anderson and E. Horvitz. Web Montage: A Dynamic Personalized Start Page, Eleventh Inernational World Wide Web Conference, Honolulu, Hawaii, May 2002.
  
  
• N. Oliver, E. Horvitz, and A. Garg. Hierarchical Representations for Learning and Inferring Office Activity from Multimodal Information, Proceedings of the IEEE Workshop on Cues in Communication, in conjunction with CVPR'01, Kuai, Hawaii, December 2001.
  
  
• E. Horvitz, Y. Ruan, C. Gomes, H. Kautz, B. Selman, D. M. Chickering. A Bayesian Approach to Tackling Hard Computational Problems. Proceedings of the Seventeenth Conference on Uncertainty and Artificial Intelligence, July 2001, pp. 235-244. Morgan Kaufmann Publishers: San Francisco.
  
  
• I. Zukerman and E. Horvitz. Using Machine Learning Techniques to Interpret WH-questions. Proceedings of Association for Computational Linguistics (ACL-2001), Toulouse, France, July 2001.
  
  
• I. Zukerman and E. Horvitz, Toward Understanding WH-Questions: A Statistical Analysis. Workshop on Machine Learning, Information Retrieval, and User Modeling, Sonthofen, Germany, July 2001.
  
  
• D. M. Pennock, E. Horvitz, S. Lawrence, and C. L. Giles. Collaborative filtering by personality diagnosis: A hybrid memory-and model-based approach, In: Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence UAI-2000), Stanford, CA, June 2000.



• E. Horvitz. Principles of Mixed-Initiative User Interfaces. Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, May 1999. more info, Lookout video, Lookout as star of a TV commercial (1999)
  
  
• E. Horvitz, A. Jacobs, D. Hovel. Attention-Sensitive Alerting, Proceedings of UAI '99, Conference on Uncertainty and Artificial Intelligence, July 1999, Morgan Kaufmann Publishers: San Francisco. pp. 305-313. video, pdf
  
  
• K. Toyama and E. Horvitz. Bayesian Modality Fusion: Probabilistic Integration of Multiple Vision Algorithms for Head Tracking. Proceedings of ACCV 2000, Fourth Asian Conference on Computer Vision, January 2000.
  
  
• David M. Pennock, Pedrito Maynard-Reid II, C. Lee Giles, and Eric Horvitz. A normative examination of ensemble learning algorithms (postscript), In: Proceedings of the 17th International Conference on Machine Learning (ICML-2000), Stanford, CA, June 2000, Morgan-Kaufmann, pp. 735-742.



• David M. Pennock, Eric Horvitz, and C. Lee Giles. Social choice theory and recommender systems: Analysis of the axiomatic foundations of collaborative filtering (postscript), to appear in Proceedings of the 17th National Conference on Artificial Intelligence (AAAI-2000), Austin, TX, July 2000.
  
  
• D.M. Pennock and E. Horvitz. Analysis of the Axiomatic Foundations of Collaborative Filtering, AAAI Workshop on Artificial Intelligence for Electronic Commerce, National Conference on Artificial Intelligence (AAAI-99), July 1999, Orlando, Florida.
  
  
• D.M. Pennock and E. Horvitz. Collaborative Filtering by Personality Diagnosis: A Hybrid Memory- and Model-Based Approach, IJCAI Workshop on Machine Learning for Information Filtering, International Joint Conference on Artificial Intelligence (IJCAI-99), August 1999, Stockholm, Sweden.
  
  
• M. Sahami, S. Dumais, D. Heckerman, and E. Horvitz. A Bayesian approach to filtering junk e-mail. AAAI Workshop on Learning for Text Categorization, July 1998, Madison, Wisconsin.
  
  
• B. Selman, R. Brooks, T. Dean, E. Horvitz, T. Mitchell, N. Nilsson. Challenge Problems for Artificial Intelligence. Proceedings of AAAI-96, Thirteenth National Conference on Artificial Intelligence, Portland, Oregon, August 1996. AAAI Press, Menlo Park, California, pp. 1340-1345 (audio available).

Human-AI complementarity and collaboration

• H. Mozannar. G. Bansal, A. Fourney, E. Horvitz, When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming, AAAI 2024, February 2024.
  
  
• A. Sellen and E. Horvitz, The Rise of the AI Co-Pilot: Lessons for Design from Aviation and Beyond, CACM 2024.
  
  
• Katelyn Morrison, Shamsi Iqbal, E. Horvitz, AI-Powered Reminders for Collaborative Tasks: Experiences and Futures, CSCW 2024.
  
  
• B. Wilder, E. Horvitz, E. Kamar. Learning to Complement Humans, IJCAI 2020.
  
  
• T. Hope, D. Downey, O. Etzioni, D.S. Weld, E. Horvitz, A Computational Inflection for Scientific Discovery, Communications of the ACM, August 2023.
  
  
• R. Fogliato, S. Chappidi, M. Lungren, et al., Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging, ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT), June 2022.
  
  
• S. Singla, B. Nushi, S. Shah, E. Kamar, E. Horvitz. Understanding Failures of Deep Networks via Robust Feature Extraction, CVPR 2021.
  
  
• E. Horvitz. Connections, Award Keynote, ACM International Conference on Multimodal Interfaces, November 2015.
  
  
• G. Bansal, B. Nushi, E. Kamar, et al. Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork, AAAI 2021.
  
  
• D. Bohus and E. Horvitz. Situated Interaction, in The Handbook of Multimodal-Multisensor Interfaces, Volume 3, ACM and Morgan & Claypool, July 2019, pp. 105-143. At ACM Digital Library
  
  
• R. Ramakrishnan, E. Kamar, D. Dey, E. Horvitz, J. Shah. Blind Spot Detection for Safe Sim-to-Real Transfer, Journal of Artificial Intelligence Research 67 (2020) 191-234.
  
  
• X.Z. Tan, S. Andrist, D. Bohus, E. Horvitz. Now, Over Here: Leveraging Extended Attentional Capabilities in Human-Robot Interaction, HRI 2020.
  
  
• G. Bansal, B. Nushi, E. Kamar, et al. Beyond Accuracy: On the Role of Mental Models in Human-AI Teams, HCOMP 2019.
  
  
• R. Ramakrishnan, E. Kamar, B. Nushi, D. Dey, J. Shah, E. Horvitz. Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution, AAAI 2019.
  
  
• S. Amershi, D. Weld, M. Vorvoreanu, A. Fourney, B. Nushi, P. Collisson, J. Suh, S. Iqbal, P.N. Bennett, K. Inkpen, J. Teevan, R. Kikin-Gil, E. Horvitz. Guidelines for Human-AI Interaction. In Proceedings of CHI 2019.
  
  
• G. Bansal, B. Nushi, E. Kamar, et al. Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff, AAAI 2019.
  
  
• R. West and E. Horvitz. Reverse-Engineering Satire, or "Paper on Computational Humor Accepted Despite Making Serious Advances", AAAI 2019.
  
  
• R. Ramakrishnan, E. Kamar, B. Nushi, D. Dey, J. Shah, E. Horvitz. Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution, AAAI 2019.
  
  
• R. Ramakrishnan, E. Kamar, D. Dey, J. Shah, E. Horvitz. Discovering Blind Spots in Reinforcement Learning, AAMAS 2018.
  
  
• B. Nushi, E. Kamar, E. Horvitz. Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure, HCOMP 2018.
  
  
• A. Segal, Y. Gal, E. Kamar, E. Horvitz, G. Miller. Optimizing Interventions via Offline Policy Evaluation: Studies in Citizen Science, AAAI 2018.
  
  
• S. Andrist, D. Bohus, E. Kamar, E. Horvitz. What Went Wrong and Why? Diagnosing Situated Interaction Failures in the Wild, ICSR 2017.
  
  
• H. Lakkaraju, E. Kamar, R. Caruana, E. Horvitz. Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration, AAAI 2017.
  
  
• B. Nushi, E. Kamar, E. Horvitz, D. Kossmann. On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems, AAAI 2017.
  
  
• D. Graus, P.N. Bennett, R.W. White, E. Horvitz. Analyzing and Predicting Task Reminders, 24th Annual Conference on User Modeling, Adaptation and Personalization (UMAP 2016), July 2016.
  
  
• A. Segal Y. Gal, E. Kamar, E. Horvitz, A. Bowyer, G. Miller. Intervention Strategies for Increasing Engagement in Crowdsourcing: Platform, Predictions, and Experiments, IJCAI 16, July 2016.
  
  
• S. Andrist, Z. Yu, D. Bohus, E. Horvitz. Are You Messing with Me? Querying about the Sincerity of Interactions in the Open World. In Proceedings of HRI 2016.
  
  
• D. Shahaf, C. Guestrin, E. Horvitz, J. Leskovec. Information Cartography, Communications of the ACM 58:11, pp. 62-73, November 2015. (View CACM video on project)
  
  
• D. Shahaf, E. Horvitz, R. Mankoff. Inside Jokes: Identifying Humorous Cartoon Captions. In Proceedings of KDD 2015.
  
  
• E. Kamar, A. Kapoor, E. Horvitz. Identifying and Accounting for Task-Dependent Bias in Crowdsourcing. In Proceedings of HCOMP 2015, Conference on Human Computation and Crowdsourcing, November 2015.
  
  
• Z. Yu, D. Bohus, E. Horvitz. Incremental Coordination: Attention-Centric Speech Production in a Physically Situated Conversational Agent. In Proceedings of Sigdial 2015.
  
  
• E. Kamar and E. Horvitz. Planning for Crowdsourcing Hierarchical Tasks. In Proceedings of AAMAS 2015.
  
  
• Ryen W. White and Eric Horvitz. Belief Dynamics and Biases in Web Search. ACM Transactions on Information Systems (ACM TOIS), 33(4), May 2015.
  
  
• D. Bohus and E. Horvitz. Managing Human-Robot Engagement with Forecasts and... um... Hesitations, ICMI 2014: International Conference on Multimodal Interaction, Istanbul, Turkey, November, 2014.
  
  
• T. Pejsa, D. Bohus, M.F. Cohen, C.W. Saw, J. Mahoney, and E. Horvitz. Natural Communication about Uncertainties in Situated Interaction, ICMI 2014: International Conference on Multimodal Interaction, Istanbul, Turkey, November, 2014 (video).
  
  
• S. Jegelka, A. Kapoor, and E. Horvitz. An Interactive Approach to Solving Correspondence Problems, International Journal of Computer Vision, Special Issue on Active and Interactive Methods in Computer Vision, 2013.
  
  
• A. Mao, E. Kamar, and E. Horvitz. Why Stop Now? Predicting Worker Engagement in Online Crowdsourcing, HCOMP 2013, Palm Springs, CA, November 2013.
  
  
• A. Mao, E. Kamar, Y. Chen, E. Horvitz, M. E. Schwamb, C.J. Lintott, and A.M. Smith. Volunteering vs. Work for Pay: Incentives and Tradeoffs in Crowdsourcing, HCOMP 2013, Palm Springs, CA, November 2013.
  
  
• D. Bohus, C.W. Saw, E. Horvitz. Directions Robot: In-the-Wild Experiences and Lessons Learned, AAMAS 2014, Paris, France, May 2014.
  
  
• S. Rosenthal, D. Bohus, E. Kamar, E. Horvitz. Look versus Leap: Computing Value of Information with High-Dimensional Streaming Evidence, IJCAI 2013, Beijing, China, August 2013.
  
  
• E. Kamar, A. Kapoor, and E. Horvitz. Lifelong Learning for Acquiring the Wisdom of the Crowd, IJCAI 2013, Beijing, China, August 2013.
  
  
• H. Zhang, E. Horvitz, D. Parkes. Automated Workflow Synthesis, AAAI 2013, Bellevue, Washington, July 2013.
  
  
• E. Kamar and E. Horvitz. Light at the End of the Tunnel: A Monte Carlo Approach to Computing Value of Information, AAMAS 2013, St. Paul, Minnesota, May 2013.
  
  
• Ryen W. White and E. Horvitz. Captions and Biases in Diagnostic Search, ACM Transactions on the Web (ACM TWEB), 2013.
  
  
• E. Kamar, S. Hacker, E. Horvitz. Combining Human and Machine Intelligence in Large-scale Crowdsourcing, AAMAS 2012, Valencia, Spain, June 2012.
  
  
• S. Rosenthal, S. Skaff, M. Veloso, D. Bohus, E. Horvitz. Execution Memory for Grounding and Coordination. Human Robot Interaction, HRI 2013, Tokyo, Japan, March 2013.
  
  
• D. Shahaf, C. Guestrin, E. Horvitz. Metro Maps for Science, KDD 2012, August 2012, Beijing, China.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Learning to Learn: Algorithmic Inspirations from Human Problem Solving, AAAI 2012, Toronto, July 2012.
  
  
• E. Kamar and E. Horvitz. Incentives for Truthful Reporting in Crowdsourcing, AAMAS 2012, Valencia, Spain, June 2012.
  
  
• D. Shahaf, C. Guestrin, E. Horvitz. Trains of Thought: Generating Information Maps, WWW 2012, Lyon, France, April 2012.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Performance and Preferences: Interactive Refinement of Machine Learning Procedures, AAAI 2012, Toronto, July 2012.
  
  
• D. Bohus, E. Kamar, E. Horvitz. Towards Situated Collaboration, NAACL 2012, Montreal, Canada, June 2012.
  
  
• H. Zhang, E. Law, K. Gajos, R. Miller, D. Parkes, and E. Horvitz. Human Computation Tasks with Global Constraints, CHI 2012, Austin, TX, May 2012.
  
  
• D. Shahaf and E. Horvitz. Generalized Task Markets for Human and Machine Computation, AAAI 2010, Atlanta, GA, July 2010.
  
  
• D. Bohus and E. Horvitz. Decisions about Turns in Multiparty Conversation: From Perception to Action, ICMI 2011: International Conference on Multimodal Interaction, Alicante, Spain, November, 2011.
  
  
• D. Bohus and E. Horvitz. Multiparty Turn Taking in Situated Dialog: Study, Lessons, and Directions, SIGDIAL 2011: Meeting on Discourse and Dialogue, Portland, OR, June, 2011.
  
  
• H. Zhang, E. Horvitz, R.C. Miller, and D.C. Parkes, Crowdsourcing General Computation Workshop on Crowdsourcing and Human Computation: Systems, Studies, and Platforms, ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Vancouver BC, May 2011.
  
  
• H. Zhang, E. Horvitz, Y. Chen, and D.C. Parkes, Task Routing for Prediction Tasks Workshop on Social Computing and User-Generated Content, EC 2011: 12th ACM Conference on Electronic Commerce , San Jose, June 2011.
  
  
• S. Seuken, D.Parkes, E. Horvitz, K. Jain, M. Czerwinski, and D. Tan, Market User Interface Design, Conference on Auctions, Market Mechanisms and their Applications(CHI), New York, NY, August 2011.
  
  
• S.T. Iqbal, E. Horvitz, Y. Ju, and E. Mathews, Hang on a Sec! Effects of Proactive Mediation of Phone Conversations while Driving, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Vancouver BC, May 2011.
  
  
• E. Kamar and E. Horvitz, Jogger: Investigation of Principles of Context-Sensitive Reminding, Proceedings of International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Tapei, May 2011.
  
  
• D. Bohus and E. Horvitz. Facilitating Multiparty Dialog with Gaze, Gesture, and Speech, ICMI-MLMI 2010: International Conference on Multimodal Interaction, Beijing, China, November, 2010.
  
  
• D. Bohus and E. Horvitz. On the Challenges and Opportunities of Physically Situated Dialog, Dialog with Robots, AAAI Fall Symposium, Arlington, VA, November, 2010.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Interactive Optimization for Steering Classification, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Atlanta, GA, April 2010.
  
  
• S.T. Iqbal, Y.C. Ju, E. Horvitz. Cars, Calls, and Cognition: Investigating Driving and Divided Attention, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Atlanta, GA, April 2010.
  
  
• D. Bohus and E. Horvitz. Models for Multiparty Engagement in Open-World Dialog, SIGDIAL 2009: Meeting on Discourse and Dialogue, London, UK, September, 2009 (video). Best Paper award.
  
  
• D. Bohus and E. Horvitz. Learning to Predict Engagement with a Spoken Dialog System in Open-World Settings, SIGDIAL 2009: Meeting on Discourse and Dialogue, London, UK, September, 2009.
  
  
• D. Bohus and E. Horvitz. Dialog in the Open World: Platform and Applications, ICMI-MLMI 2009: International Conference on Multimodal Interaction, Cambridge, MA. November, 2009. Outstanding Paper award.
  
  
• S.T. Iqbal and E. Horvitz. Notifications and Awareness: A Field Study of Alert Usage and Preferences, Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW), Savannah, GA, February 2010.
  
  
• D. Bohus and E. Horvitz. Open-World Dialog: Challenges, Directions, and a Prototype. IJCAI Workshop on Knowledge and Reasoning in Practical Dialog Systems, Pasadena, CA, August 2009 (video).
  
  
• A. Kapoor, D. Tan, P. Shenoy, E. Horvitz. Complementary Computing for Visual Tasks: Meshing Computer Vision with Human Visual Processing, IEEE International Conference on Automatic Face and Gesture Recognition.
  
  
• A. Kapoor and E. Horvitz. Experience Sampling for Building Predictive User Models: A Comparative Study, Proceedings of CHI 2008, Florence, Italy, April 2008.
  
  
• E. Horvitz. Reflections on Challenges and Promises of Mixed-Initiative Interaction, AAAI Magazine 28, Special Issue on Mixed-Initiative Assistants (2007).
  
  
• E. Horvitz and T. Paek. Complementary Computing: Policies for Transferring Callers from Dialog Systems to Human Receptionists. User Modeling and User Adapted Interaction 17 (2007).
  
  
• S. Iqbal and E. Horvitz. Conversations Amidst Computing: A Study of Interruptions and Recovery of Task Activity. Proceedings of the Eleventh Conference on User Modeling (UM 2005), June 2007, Corfu, Greece.
  
  
• E. Horvitz, J. Apacible, and P. Koch. BusyBody: Creating and Fielding Personalized Models of the Cost of Interruption, Proceedings of CSCW, Conference on Computer Supported Cooperative Work, ACM Press, November 2004.
  
  
• E. Horvitz and J. Apacible. Learning and Reasoning about Interruption. Proceedings of the Fifth ACM International Conference on Multimodal Interfaces, November 2003, Vancouver, BC, Canada.
  
  
• E. Horvitz, J. Apacible, M. Subramani. Balancing Awareness and Interruption: Investigation of Notification Deferral Policies. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• N. Oliver and E. Horvitz. A Comparison of HMMs and Dynamic Bayesian Networks for Recognizing Office Activities. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• T. Paek and E. Horvitz. Optimizing Automated Call Routing by Integrating Spoken Dialog Models with Queuing Models, HLT 2004: Human Language Technology Conference, May 2004.
  
  
• E. Horvitz, S. Dumais, P. Koch. Learning Predictive Models of Memory Landmarks, CogSci 2004: 26th Annual Meeting of the Cognitive Science Society, Chicago, August 2004.
  
  
• N. Oliver and E. Horvitz. Selective Perception Policies for Limiting Computation in Multimodal Systems: A Comparative Analysis, Proceedings of the Fifth ACM International Conference on Multimodal Interfaces, November 2003, Vancouver, BC, Canada.
  
  
• N. Oliver, A. Garg, and Eric Horvitz. Layered Representations for Learning and Inferring Office Activity from Multiple Sensory Channels, Computer Vision and Image Understanding (CVIU), 96(2004), pp. 163-180.
  
  
• E. Horvitz, C. M. Kadie, T. Paek, D. Hovel. Models of Attention in Computing and Communications: From Principles to Applications, Communications of the ACM 46(3):52-59, March 2003. More information.   Video: Directions & futures   Video: Priorities & Notification Platform, photo.
  
  
• M. Ringel, E. Cutrell, S. Dumais, E. Horvitz. Milestones in Time: The Value of Landmarks in Retrieving Information from Personal Stores. Proceedings of Interact 2003: Ninth International Conference on Human-Computer Interaction, September 2003, Z rich, Switzerland.
  
  
• U. Nodelman and E. Horvitz, Continuous Time Bayesian Networks for Inferring Users Presence and Activities with Extensions for Modeling and Evaluation, Microsoft Research Technical Report MSR-TR-2003-97, December 2003.
  
  
• T. Paek and E. Horvitz, On the Utility of Decision-Theoretic Hidden Subdialog. In Proceedings of International Speech Communication Association (ISCA) Workshop on Error Handling in Spoken Dialogue Systems, Chateaux d'Oex, Switzerland, August 2003.
  
  
• K. Hinckley, J. Pierce, E. Horvitz, M. Sinclair. Foreground and Background Interaction with Sensor-enhanced Mobile Devices, Transactions on Computer-Human Interaction (ACM TOCHI), Special Issue on Sensor-Based Interaction, 12 (1), March 2005, pp. 31-52.
  
  
• N. Oliver, E. Horvitz, and A. Garg. Layered Representations for Recognizing Office Activity, Proceedings of the Fourth IEEE International Conference on Multimodal Interaction (ICMI 2002), October 2002, Pittsburgh, PA, pp.3-8
  
  
• E. Horvitz, P. Koch, C.M. Kadie, and A. Jacobs. Coordinate: Probabilistic Forecasting of Presence and Availability.Proceedings of UAI '02, Proceedings of the Eighteenth Conference on Uncertainty and Artificial Intelligence, Edmonton, Canada, July 2002, pp. 224-233.
  
  
• C. R. Anderson and E. Horvitz. Web Montage: A Dynamic Personalized Start Page, Eleventh Inernational World Wide Web Conference, Honolulu, Hawaii, May 2002.
  
  
• E. Horvitz and T. Paek. Harnessing Models of Users' Goals to Mediate Clarification Dialog in Spoken Language Systems. Proceedings of the Eighth International Conference on User Modeling, July 2001.
  
  
• E. Horvitz. Uncertainty, Action, and Interaction: In Pursuit of Mixed-Initiative Computing. Intelligent Systems, Sept./ October Issue, 2000, IEEE Computer Society.
  
  
• T. Paek, E. Horvitz, E. Ringger. Continuous Listening for Unconstrained Spoken Dialog, 6th International Conference on Spoken Language Processing (ICSLP 2000), Beijing, November 2000.
  
  
• E. Horvitz and T. Paek, DeepListener: Harnessing Expected Utility to Guide Clarification Dialog in Spoken Language Systems, 6th International Conference on Spoken Language Processing (ICSLP 2000), Beijing, November 2000.
  
  
• E. Horvitz. Principles of Mixed-Initiative User Interfaces. Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, May 1999. more info, Lookout video, Lookout as star of a TV commercial (1999)
  
  
• E. Horvitz. Uncertainty, Action, and Interaction: In Pursuit of Mixed-Initiative Computing. Intelligent Systems, Sept./ October Issue, IEEE Computer Society.
  
  
• E. Horvitz, A. Jacobs, D. Hovel. Attention-Sensitive Alerting, Proceedings of UAI '99, Conference on Uncertainty and Artificial Intelligence, July 1999, Morgan Kaufmann Publishers: San Francisco. pp. 305-313. pdf, video
  
  
• K. Hinckley, J. Pierce, M. Sinclair, E. Horvitz, Sensing Techniques for Mobile Interaction, ACM UIST 2000 Symposium on User Interface Software and Technology, November 2000, San Diego, California, pp. 91-100. (Best Paper award, 2010; Lasting Impact award, 2011.) Video demo (mpeg).
  
  
• E. Horvitz and J. Lengyel. Perception, Attention, and Resources: A Decision-Theoretic Approach to Graphics Rendering. Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, August 1997, Morgan Kaufman: San Francisco, pp. 238-249.
  
  
• T. Lau and E. Horvitz, Patterns of Search: Analyzing and Modeling Web Query Refinement. Proceedings of the Seventh International Conference on User Modeling, Banff, Canada, June 1999. New York: Springer Wien.
  
  
• E. Horvitz and T. Paek, A Computational Architecture for Conversation. Proceedings of the Seventh International Conference on User Modeling, Banff, Canada, June 1999. New York: Springer Wien.
  
  
• T. Paek and Eric Horvitz. Conversation as Action Under Uncertainty, In Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence (UAI-2000), Stanford, CA, June 2000.
  
  
• T. Paek and E. Horvitz, Uncertainty, Utility, and Misunderstanding: A Decision-Theoretic Perspective on Grounding in Conversational Systems. AAAI Fall Symposium on Psychological Models of Communication in Collaborative Systems, Cape Cod, MA. November 5-7, 1999.
  
  
• T. Paek and E. Horvitz, Grounding Criterion: Toward a Formal Theory of Grounding. MSR Technical Report MSR-TR-2000-40, April 1999.
  
  
• E. Horvitz, J. Breese, D. Heckerman, D. Hovel, and K. Rommelse. The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July 1998, Morgan Kaufmann: San Francisco, pp. 256-265.   Video   More on Lumiere.
  
  
• D. Heckerman and E. Horvitz. Inferring Informational Goals from Free-Text Queries. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July 1998, Morgan Kaufmann: San Francisco, pp. 230-237.
  
  
• L. Birnbaum, E. Horvitz, D.J. Kurlander, H. Lieberman, J. Marks, S. Roth, Compelling intelligent user interfaces how much AI?, Proceedings of the 2nd international conference on Intelligent user interfaces (IUI '97), January 1997, pp. 173 175.
  
  
• E. Horvitz and M Barry. Display of Information for Time-Critical Decision Making. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, August 1995 (pdf).
  
  
• E. Horvitz and M. Shwe, Handsfree Decision Support: Toward a Non-invasive Human-Computer Interface, Nineteenth Annual Symposium on Computer Applications in Medical Care. Toward Cost-Effective Clinical Computing, November 1995. View photo and videos of early prototype.
  
  
• E. Horvitz. Innovations at the Human Computer Interface: A Medical-Informatics Perspective, In Proceedings of MMVR I, Medicine Meets Virtual Reality I, San Diego, June 1992.
  
  
• E. Horvitz, D. Heckerman, K. Ng, B. Nathwani, Heuristic Abstraction in the Decision-Theoretic Pathfinder System, Symposium on Computer Applications in Medical Care, Washington DC, IEEE Press: Silver Springs, MD, November 1989.
  
  
• E.J. Horvitz, Toward a Science of Expert Systems, In: Proceedings of the 18th Symposium on the Interface of Statistics and Computer Science, Fort Collins, Colorado, March 1986, Thomas J. Boardman, Editor, American Statistical Association: Washington, D.C., pp. 45-52 (pdf).
  
  
• E. Horvitz, D. Heckerman, B. Nathwani, L.M. Fagan, The use of a heuristic problem-solving hierarchy to facilitate the explanation of hypothesis-directed reasoning, October 1986, In: Proceedings of Medinfo, Washington, DC, North Holland: New York, pp. 27-31.
  
  
• E.J. Horvitz, D.E. Heckerman, B.N. Nathwani, L.M. Fagan, Diagnostic Strategies in the Hypothesis-Directed Pathfinder System, In: Proceedings of the First Conference on Artificial Intelligence Applications, Denver, Colorado, December 1984. IEEE Computer Society, Computer Society Press, pp. 630-636 (pdf).
  
  

Dialog and situated interaction

• D. Bohus, S. Andrist, A. Feniello, N. Saw, E. Horvitz, Continual Learning about Objects in the Wild: An Interactive Approach, International Conference on Multimodal Interaction (ICMI), November 2022.
  
  
• E. Horvitz, On the Horizon: Interactive and Compositional Deepfakes, International Conference on Multimodal Interaction (ICMI), November 2022. video
  
  
• X.Z. Tan, S. Andrist, D. Bohus, E. Horvitz. Now, Over Here: Leveraging Extended Attentional Capabilities in Human-Robot Interaction, HRI 2020.
  
  
• D. Bohus and E. Horvitz. Situated Interaction, in The Handbook of Multimodal-Multisensor Interfaces, Volume 3, ACM and Morgan & Claypool, July 2019, pp. 105-143.
  
  
• J. Zhang, J.W. Pennebaker, S.T. Dumais, E. Horvitz. Configuring Audiences: A Case Study of Email Communication. CSCW 2020.
  
  
• S. Andrist, D. Bohus, E. Kamar, E. Horvitz. What Went Wrong and Why? Diagnosing Situated Interaction Failures in the Wild, ICSR 2017.
  
  
• S. Andrist, Z. Yu, D. Bohus, E. Horvitz. Are You Messing with Me? Querying about the Sincerity of Interactions in the Open World. In Proceedings of HRI 2016.
  
  
• Z. Yu, D. Bohus, E. Horvitz. Incremental Coordination: Attention-Centric Speech Production in a Physically Situated Conversational Agent. In Proceedings of Sigdial 2015.
  
  
• D. Bohus and E. Horvitz. Managing Human-Robot Engagement with Forecasts and... um... Hesitations, ICMI 2014: International Conference on Multimodal Interaction, Istanbul, Turkey, November, 2014.
  
  
• T. Pejsa, D. Bohus, M.F. Cohen, C.W. Saw, J. Mahoney, and E. Horvitz. Natural Communication about Uncertainties in Situated Interaction, ICMI 2014: International Conference on Multimodal Interaction, Istanbul, Turkey, November, 2014 (video).
  
  
• D. Bohus, C.W. Saw, E. Horvitz. Directions Robot: In-the-Wild Experiences and Lessons Learned, AAMAS 2014, Paris, France, May 2014.
  
  
• S. Rosenthal, D. Bohus, E. Kamar, E. Horvitz. Look versus Leap: Computing Value of Information with High-Dimensional Streaming Evidence, IJCAI 2013, Beijing, China, August 2013.
  
  
• W. Wang, D. Bohus, E. Kamar, E. Horvitz. Crowdsourcing the Acquisition of Natural Language Corpora: Methods and Observations, SLT 2012 - IEEE Spoken Language Technologies, Miami, FA, December 2012.
  
  
• S. Rosenthal, S. Skaff, M. Veloso, D. Bohus, E. Horvitz. Execution Memory for Grounding and Coordination. Human Robot Interaction, HRI 2013, Tokyo, Japan, March 2013.
  
  
• D. Bohus, E. Kamar, E. Horvitz. Towards Situated Collaboration, NAACL 2012, Montreal, Canada, June 2012.
  
  
• D. Bohus and E. Horvitz. Decisions about Turns in Multiparty Conversation: From Perception to Action, ICMI 2011: International Conference on Multimodal Interaction, Alicante, Spain, November, 2011.
  
  
• D. Bohus and E. Horvitz. Multiparty Turn Taking in Situated Dialog: Study, Lessons, and Directions, SIGDIAL 2011: Meeting on Discourse and Dialogue, Portland, OR, June, 2011.
  
  
• D. Bohus and E. Horvitz. Facilitating Multiparty Dialog with Gaze, Gesture, and Speech, ICMI-MLMI 2010: International Conference on Multimodal Interaction, Beijing, China, November, 2010.
  
  
• D. Bohus and E. Horvitz. On the Challenges and Opportunities of Physically Situated Dialog, Dialog with Robots, AAAI Fall Symposium, Arlington, VA, November, 2010.
  
  
• D. Bohus and E. Horvitz. Models for Multiparty Engagement in Open-World Dialog, SIGDIAL 2009: Meeting on Discourse and Dialogue, London, UK, September, 2009 (video). Best Paper award.
  
  
• D. Bohus and E. Horvitz. Learning to Predict Engagement with a Spoken Dialog System in Open-World Settings, SIGDIAL 2009: Meeting on Discourse and Dialogue, London, UK, September, 2009.
  
  
• D. Bohus and E. Horvitz. Dialog in the Open World: Platform and Applications, ICMI-MLMI 2009: International Conference on Multimodal Interaction, Cambridge, MA. November, 2009. Outstanding Paper award.
  
  
• D. Bohus and E. Horvitz. Open-World Dialog: Challenges, Directions, and a Prototype. IJCAI Workshop on Knowledge and Reasoning in Practical Dialog Systems, Pasadena, CA, August 2009 (video).
  
  
• E. Horvitz. Reflections on Challenges and Promises of Mixed-Initiative Interaction, AAAI Magazine 28, Special Issue on Mixed-Initiative Assistants (2007).
  
  
• T. Paek and E. Horvitz, On the Utility of Decision-Theoretic Hidden Subdialog. In Proceedings of International Speech Communication Association (ISCA) Workshop on Error Handling in Spoken Dialogue Systems, Chateaux d'Oex, Switzerland, August 2003.
  
  
• E. Horvitz and T. Paek. Harnessing Models of Users' Goals to Mediate Clarification Dialog in Spoken Language Systems. Proceedings of the Eighth International Conference on User Modeling, July 2001.
  
  
• T. Paek, E. Horvitz, E. Ringger. Continuous Listening for Unconstrained Spoken Dialog, 6th International Conference on Spoken Language Processing (ICSLP 2000), Beijing, November 2000.
  
  
• E. Horvitz and T. Paek, DeepListener: Harnessing Expected Utility to Guide Clarification Dialog in Spoken Language Systems, 6th International Conference on Spoken Language Processing (ICSLP 2000), Beijing, November 2000.
  
  
• E. Horvitz. Principles of Mixed-Initiative User Interfaces. Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, May 1999. more info, Lookout video, Lookout as star of a TV commercial (1999)
  
  
• E. Horvitz. Uncertainty, Action, and Interaction: In Pursuit of Mixed-Initiative Computing. Intelligent Systems, Sept./ October Issue, IEEE Computer Society.
  
  
• E. Horvitz and T. Paek, A Computational Architecture for Conversation. Proceedings of the Seventh International Conference on User Modeling, Banff, Canada, June 1999. New York: Springer Wien.
  
  
• T. Paek and Eric Horvitz. Conversation as Action Under Uncertainty, In Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence (UAI-2000), Stanford, CA, June 2000.



• T. Paek and E. Horvitz, Uncertainty, Utility, and Misunderstanding: A Decision-Theoretic Perspective on Grounding in Conversational Systems. AAAI Fall Symposium on Psychological Models of Communication in Collaborative Systems, Cape Cod, MA. November 5-7, 1999.
  
  
• T. Paek and E. Horvitz, Grounding Criterion: Toward a Formal Theory of Grounding. MSR Technical Report MSR-TR-2000-40, April 1999.
  
  
• E. Horvitz and M. Shwe, Handsfree Decision Support: Toward a Non-invasive Human-Computer Interface, Nineteenth Annual Symposium on Computer Applications in Medical Care. Toward Cost-Effective Clinical Computing, November 1995. View photo and videos of early prototype.
  
  

Interaction and Cognition

• M. Sap, A. Jafarpour, Y. Choi, N.A. Smith, J.W. Pennebaker, E. Horvitz. Imagined versus Remembered Stories: Quantifying Differences in Narrative Flows, Proceedings of the National Academy of Sciences (PNAS), 2022.
  
  
• S. Singla, B. Nushi, S. Shah, E. Kamar, E. Horvitz. Understanding Failures of Deep Networks via Robust Feature Extraction, CVPR 2021.
• D. Bohus and E. Horvitz. Situated Interaction, in The Handbook of Multimodal-Multisensor Interfaces, Volume 3, ACM and Morgan & Claypool, July 2019, pp. 105-143.
  
  
• B. Wilder, E. Horvitz, E. Kamar. Learning to Complement Humans, IJCAI 2020.
  
  
• M. Sap, E. Horvitz, Y. Choi, N.A. Smith, J.W. Pennebaker. Recollection versus Imagination: Exploring Human Memory and Cognition via Neural Language Models, ACL 2020.
  
  
• J. Zhang, J.W. Pennebaker, S.T. Dumais, E. Horvitz. Configuring Audiences: A Case Study of Email Communication. CSCW 2020.
  
  
• S. Amershi, D. Weld, M. Vorvoreanu, A. Fourney, B. Nushi, P. Collisson, J. Suh, S. Iqbal, P.N. Bennett, K. Inkpen, J. Teevan, R. Kikin-Gil, E. Horvitz. Guidelines for Human-AI Interaction. In Proceedings of CHI 2019.
  
  
• D. Shahaf, E. Horvitz, R. Mankoff. Inside Jokes: Identifying Humorous Cartoon Captions. In Proceedings of KDD 2015.
  
  
• D. Graus, P.N. Bennett, R.W. White, E. Horvitz. Analyzing and Predicting Task Reminders, 24th Annual Conference on User Modeling, Adaptation and Personalization (UMAP 2016), July 2016.
  
  
• A. Segal Y. Gal, E. Kamar, E. Horvitz, A. Bowyer, G. Miller. Intervention Strategies for Increasing Engagement in Crowdsourcing: Platform, Predictions, and Experiments, IJCAI 16, July 2016.
  
  
• Z. Yu, D. Bohus, E. Horvitz. Incremental Coordination: Attention-Centric Speech Production in a Physically Situated Conversational Agent. In Proceedings of Sigdial 2015.
  
  
• Ryen W. White and Eric Horvitz. Belief Dynamics and Biases in Web Search. ACM Transactions on Information Systems (ACM TOIS), 33(4), May 2015.
  
  
• M. De Choudhury, M. Gamon, S. Counts, E. Horvitz. Predicting Depression via Social Media, ICWSM 2013, Boston, MA, July 2013.
  
  
• R. West, R.W. White, E. Horvitz, From Cookies to Cooks: Insights on Dietary Patterns via Analysis of Web Usage Logs, WWW 2013, Rio de Janeiro, Brazil, May 2013.
  
  
• M. De Choudhury, S. Counts, E. Horvitz. Social Media as a Measurement Tool of Depression in Populations, WebSci 2013, May 2013, Paris, France.
  
  
• M. De Choudhury, S. Counts, E. Horvitz. Predicting Postpartum Changes in Emotion and Behavior via Social Media, CHI 2013, April 2013, Paris, France.
  
  
• R.W. White, N.P. Tatonetti, N. H. Shah, R.B. Altman, E. Horvitz. Web-Scale Pharmacovigilance: Listening to Signals from the Crowd. JAMIA, March 2013.
  
  
• S. Rosenthal, S. Skaff, M. Veloso, D. Bohus, E. Horvitz. Execution Memory for Grounding and Coordination. Human Robot Interaction, HRI 2013, Tokyo, Japan, March 2013.
  
  
• M. De Choudhury, S. Counts, E. Horvitz. Major Life Changes and Behavioral Markers in Social Media: Case of Childbirth, CSCW 2013, February 2013, San Antonio, Texas.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Learning to Learn: Algorithmic Inspirations from Human Problem Solving, AAAI 2012, Toronto, July 2012.
  
  
• M. De Choudhury, S. Counts, E. Horvitz. How Social Information Networks Reflect Major Life Events: Case of Childbirth, Workshop on Information in Networks (WIN), New York, NY, September 2012.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Performance and Preferences: Interactive Refinement of Machine Learning Procedures, AAAI 2012, Toronto, July 2012
  
  
• A. Krause and E. Horvitz. A Utility-theoretic Approach to Privacy in Online Services, Journal of Artificial Intelligence Research, 39 (2010) 633-662.
  
  
• S. Seuken, D.Parkes, E. Horvitz, K. Jain, M. Czerwinski, and D. Tan, Market User Interface Design, Conference on Auctions, Market Mechanisms and their Applications(CHI), New York, NY, August 2011.
  
  
• S.T. Iqbal, J. Grudin, E. Horvitz, Peripheral computing during presentations: Perspectives on costs and preferences, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), pp 891 894, Vancouver, BC, May 2011. https://doi.org/10.1145/1978942.1979073
  
  
• S.T. Iqbal, J. Grudin, E. Horvitz, Divided Attention=Diminished Uptake? Multitasking with Computing Devices at Presentations, Microsoft Research Technical Report, MSR-TR-2009-155, November 2009.
  
  
• S.T. Iqbal, E. Horvitz, Y. Ju, and E. Mathews, Hang on a Sec! Effects of Proactive Mediation of Phone Conversations while Driving, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Vancouver BC, May 2011.
  
  
• E. Kamar and E. Horvitz, Jogger: Investigation of Principles of Context-Sensitive Reminding, Proceedings of International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Tapei, May 2011.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Interactive Optimization for Steering Classification, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Atlanta, GA, April 2010.
  
  
• S.T. Iqbal, Y.C. Ju, E. Horvitz. Cars, Calls, and Cognition: Investigating Driving and Divided Attention, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Atlanta, GA, April 2010.
  
  
• S.T. Iqbal and E. Horvitz. Notifications and Awareness: A Field Study of Alert Usage and Preferences, Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW), Savannah, GA, February 2010.
  
  
• B. Bailey, E. Horvitz. What s Your Idea? A Case Study of a Grassroots Innovation Pipeline within a Large Software Company, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Atlanta, GA, April 2010.
  
  
• M. Bernstein, D. Tan, G. Smith, M. Czerwinski, Eric Horvitz. Collabio: A Game for Annotating People within Social Networks. Proceedings of UIST 2009. Victoria, Canada, October 2009 (video).
  
  
• E. Horvitz and B. Selman. AAAI Presidential Panel on Long-Term AI Futures: Interim Report from the Panel Chairs, Association for the Advancement of Artificial Intelligence, August 2009. In: A. H. Eden, J.H. Moor, J.H.Soraker, and E. Steinhart, Eds., Singularity Hypotheses: A Scientific and Philosophical Assessment, 2013.
  
  
• A. Krause and E. Horvitz. A Utility-Theoretic Approach to Privacy and Personalization, AAAI-08: Twenty-Third Conference on Artificial Intelligence, Chicago, Illinois, July 2008.
  
  
• A. Kapoor, D. Tan, P. Shenoy, E. Horvitz. Complementary Computing for Visual Tasks: Meshing Computer Vision with Human Visual Processing, IEEE International Conference on Automatic Face and Gesture Recognition.
  
  
• J. Leskovec and E. Horvitz. Planetary-Scale Views on a Large Instant-Messaging Network, Proceedings of WWW 2008, Beijing, China, April 2008. (CNBC discussion)
  
  
• A. Krause and E. Horvitz. Privacy, Personalization, and the Web: A Utility-theoretic Approach, NIPS Workshop on Machine Learning for Web Search, Whistler, British Columbia, December 2007.
  
  
• A. Kapoor and E. Horvitz. On Discarding, Caching, and Recalling Samples in Active Learning, Proceedings of the Conference on Uncertainty and Artificial Intelligence 2007, AUAI Press, July 2007.
  
  
• J. Leskovec and E. Horvitz. Worldwide Buzz: Planetary-Scale Views on an Instant-Messaging Network, Microsoft Research Technical Report MSR-TR-2006-186, Microsoft Research, June 2007. (MSNBC discussion)
  
  
• M. R. Morris and E. Horvitz. S3: Storable, Shareable Search, Proceedings of Interact 2007, Proceedings of Interact 2007, Riao De Janeiro, Brazil, September 2007.
  
  
• D. Downey, S. Dumais, and E. Horvitz. Heads and Tails: Studies of Web Search with Common and Rare Queries, Proceedings of SIGIR 2007, ACM Press, August 2007.
  
  
• M. R. Morris and E. Horvitz. SearchTogether: An Interface for Collaborative Web Search, Proceedings of UIST 2007, Newport, RI, October 2007.
  
  
• E. Horvitz. Reflections on Challenges and Promises of Mixed-Initiative Interaction, AAAI Magazine 28, Special Issue on Mixed-Initiative Assistants (2007).
  
  
• S. T. Iqbal and E. Horvitz. Disruption and Recovery of Computing Tasks: Field Study, Analysis, and Directions, Proceedings of CHI 2007, San Jose, California, April 2007.
  
  
• E. Horvitz and T. Paek. Complementary Computing: Policies for Transferring Callers from Dialog Systems to Human Receptionists. User Modeling and User Adapted Interaction 17 (2007).
  
  
• E. Horvitz and P. Koch. Mobile Opportunistic Planning: Methods and Models. Proceedings of the Eleventh Conference on User Modeling (UM 2005), June 2007, Corfu, Greece, pp. 238 247.
  
  
• E Horvitz. Machine Learning, Reasoning, and Intelligence in Daily Life: Directions and Challenges (Invited talk), Proceedings of Artificial Intelligence Techniques for Ambient Intelligence, Hyderabad, India, January 2007.
  
  
• A. Kapoor and E. Horvitz. Principles of Lifelong Learning for Predictive User Modeling. Proceedings of the Eleventh Conference on User Modeling (UM 2005), June 2007, Corfu, Greece.
  
  
• J.C. Krumm and E. Horvitz. Driver Destination Models. Proceedings of the Eleventh Conference on User Modeling (UM 2005), June 2007, Corfu, Greece.
  
  
• S. Iqbal and E. Horvitz. Conversations Amidst Computing: A Study of Interruptions and Recovery of Task Activity. Proceedings of the Eleventh Conference on User Modeling (UM 2005), June 2007, Corfu, Greece.
  
  
• P. Dewan, J. Grudin, E. Horvitz. Towards Mixed-Initiative Access Control, Proceedings of the IEEE Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2007), November 2007, 64-71.
  
  
• J. Krumm and E Horvitz. Predestination: Inferring Destinations from Partial Trajectories, UbiComp 2006: Eighth International Conference on Ubiquitous Computing, September 2006.
  
  
• J. Letchner, J. Krumm, and E. Horvitz, Trip Router with Individualized Preferences: Incorporating Personalization into Route Planning, Eighteenth Conference on Innovative Applications of Artificial Intelligence, July 2006.
  
  
• E. Horvitz, Reflection: Expectations in 50 years, New Scientist, 50th Anniversary Edition, November 2006.
  
  
• E. Horvitz, J. Apacible, R. Sarin, and L. Liao. Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service, Proceedings of the Conference on Uncertainty and Artificial Intelligence 2005,, AUAI Press, July 2005.
  
  
• E. Horvitz, J. Apacible, and P. Koch. BusyBody: Creating and Fielding Personalized Models of the Cost of Interruption, Proceedings of CSCW, Conference on Computer Supported Cooperative Work, ACM Press, November 2004.
  
  
• E. Horvitz and J. Apacible. Learning and Reasoning about Interruption. Proceedings of the Fifth ACM International Conference on Multimodal Interfaces, November 2003, Vancouver, BC, Canada.
  
  
• E. Horvitz, J. Apacible, M. Subramani. Balancing Awareness and Interruption: Investigation of Notification Deferral Policies. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• N. Oliver and E. Horvitz. A Comparison of HMMs and Dynamic Bayesian Networks for Recognizing Office Activities. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• E. Horvitz, P. Koch, R. Sarin, J. Apacible, M. Subramani. Bayesphone: Context-Sensitive Policies for Inquiry and Action in Mobile Devices. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• R. Hariharan, J. Krumm, E. Horvitz, Web-Enhanced GPS, Proceedings of the International Workshop on Location- and Context-Awareness (LoCA 2005), May 2005.
  
  
• J. Olson, J. Grudin, E. Horvitz. A Study of Preferences for Sharing and Privacy. ACM SIGCHI Conference on Human Factors in Computing Systems, Portland, OR , April, 2005.
  
  
• T. Paek and E. Horvitz. Optimizing Automated Call Routing by Integrating Spoken Dialog Models with Queuing Models, HLT 2004: Human Language Technology Conference, May 2004.
  
  
• E. Horvitz, S. Dumais, P. Koch. Learning Predictive Models of Memory Landmarks, CogSci 2004: 26th Annual Meeting of the Cognitive Science Society, Chicago, August 2004.
  
  
• E. Horvitz, A Curse of Riches or a Blessing? Information Access and Awareness under Scarce Cognitive Resources, Keynote abstract, Adaptive Hypermedia 2004, Eindhoven, Netherlands, August 2004.
  
  
• G. Robertson, E. Horvitz, M. Czerwinski, P. Baudisch, D. Hutchings, B. Meyers, D. Robbins, G. Smith, Scalable Fabric: A Flexible Representation for Task Management, Advanced Visual Interfaces, AVI 2004, Gallipoli, Italy, May 2004, pp. 85-89.
  
  
• D. Robbins, E. Cutrell, R. Sarin, E. Horvitz, ZoneZoom: Map Navigation with Smartphones with Recursive View Segmentation, Advanced Visual Interfaces, AVI 2004, Gallipoli, Italy, May 2004.
  
  
• M. Czerwinski, M., E. Horvitz, and S. Wilhite. A Diary Study of Task Switching and Interruptions, Proceedings of CHI 2004, Human Factors in Computing Systems. Vienna, April 2004.
  
  
• E. Horvitz, C. M. Kadie, T. Paek, D. Hovel. Models of Attention in Computing and Communications: From Principles to Applications, Communications of the ACM 46(3):52-59, March 2003. More information.   Video: Directions & futures   Video: Priorities & Notification Platform, photo.
  
  
• M. Ringel, E. Cutrell, S. Dumais, E. Horvitz. Milestones in Time: The Value of Landmarks in Retrieving Information from Personal Stores. Proceedings of Interact 2003: Ninth International Conference on Human-Computer Interaction, September 2003, Z rich, Switzerland.
  
  
• K. Hinckley, J. Pierce, E. Horvitz, M. Sinclair. Foreground and Background Interaction with Sensor-enhanced Mobile Devices, Transactions on Computer-Human Interaction (ACM TOCHI), Special Issue on Sensor-Based Interaction, 12 (1), March 2005, pp. 31-52.
  
  
• Czerwinski, M. and Horvitz, E. An Investigation of Memory for Daily Computing Events. Proceedings of HCI 2002: Sixteenth British HCI Group Annual Conference, London, England, September 2002.
  
  
• E. Horvitz, P. Koch, C.M. Kadie, and A. Jacobs. Coordinate: Probabilistic Forecasting of Presence and Availability.Proceedings of UAI '02, Proceedings of the Eighteenth Conference on Uncertainty and Artificial Intelligence, Edmonton, Canada, July 2002, pp. 224-233.
  
  
• M. van Dantzich, D. Robbins, E. Horvitz, M. Czerwinski, Scope: Providing Awareness of Multiple Notifications at a Glance, In: Proceedings of AVI 2002, ACM Conference on Advanced Visual Interfaces, Trento, Italy, May 22-24, 2002. ACM Press.
  
  
• C. R. Anderson and E. Horvitz. Web Montage: A Dynamic Personalized Start Page, Eleventh Inernational World Wide Web Conference, Honolulu, Hawaii, May 2002.
  
  
• Horvitz, E., Apacible, J., Subramani, M., Sarin, R., Koch, P., Cadiz, J.J., Narin, A., Rui, Y., Experiences with the Design, Fielding, and Evaluation of a Real-Time Communications Agent, Microsoft Research Technical Report MSR-TR-2003-98, December 2003.
  
  
• E. Cutrell, M. Czerwinski, and E. Horvitz. Notification, Disruption and Memory: Effects of Messaging Interruptions on Memory and Performance. Proceedings of Interact 2001, Tokyo.
  
  
• M. Czerwinski, E. Horvitz, and E. Cutrell. Subjective Duration Assessment: An Implicit Probe for Software Usability. Proceedings of IHM-HCI 2001, Lille, France, September, 2001, pp. 167-170.
  
  
• E. Horvitz. Uncertainty, Action, and Interaction: In Pursuit of Mixed-Initiative Computing. Intelligent Systems, Sept./ October Issue, 2000, IEEE Computer Society.
  
  
• M. Czerwinski, E. Cutrell, and E. Horvitz. Instant Messaging and Interruption: Influence of Task Type on Performance, Proceedings of OZCHI 2000, Sydney, Australia, December 2000.
  
  
• M. Czerwinski, E. Cutrell, and E. Horvitz. Instant Messaging: Effects of Relevance and Time, In S. Turner, P. Turner (Eds), People and Computers XIV: Proceedings of HCI 2000, Sunderland, UK, September 2000. Vol. 2, British Computer Society, p. 71-76.
  
  
• E. Cutrell, M. Czerwinski, and E. Horvitz. Effects of Instant Messaging Interruptions on Computing Tasks. In Extended Abstracts of CHI ’2000, Human Factors in Computing Systems, The Hague, April 1-6, 2000, ACM press, 99-100. ACM Press.
  
  
• E. Horvitz. Principles of Mixed-Initiative User Interfaces. Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, May 1999. more info, Lookout video, Lookout as star of a TV commercial (1999)
  
  
• E. Horvitz. Uncertainty, Action, and Interaction: In Pursuit of Mixed-Initiative Computing. Intelligent Systems, Sept./ October Issue, IEEE Computer Society.
  
  
• E. Horvitz, A. Jacobs, D. Hovel. Attention-Sensitive Alerting, Proceedings of UAI '99, Conference on Uncertainty and Artificial Intelligence, July 1999, Morgan Kaufmann Publishers: San Francisco. pp. 305-313. pdf, video
  
  
• K. Hinckley, J. Pierce, M. Sinclair, E. Horvitz, Sensing Techniques for Mobile Interaction, ACM UIST 2000 Symposium on User Interface Software and Technology, November 2000, San Diego, California, pp. 91-100. (Best Paper award, 2010; Lasting Impact award, 2011.) Video demo (mpeg).
  
  
• K. Larson, E. Horvitz, J. Lengyel, M. Czerwinski. Applied Psychophysics: Studies in Support of Perception-Directed Graphics Rendering, Microsoft Research Technical Report, Fall 1997.
  
  
• E. Horvitz and J. Lengyel. Perception, Attention, and Resources: A Decision-Theoretic Approach to Graphics Rendering. Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, August 1997, Morgan Kaufman: San Francisco, pp. 238-249.
  
  
• E. Horvitz, J. Breese, D. Heckerman, D. Hovel, and K. Rommelse. The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July 1998, Morgan Kaufmann: San Francisco, pp. 256-265.   Video   More on Lumiere.
  
  

Human computation and crowdsourcing

• M. Sap, E. Horvitz, Y. Choi, N.A. Smith, J.W. Pennebaker. Recollection versus Imagination: Exploring Human Memory and Cognition via Neural Language Models, ACL 2020.
  
  
• R. Ramakrishnan, E. Kamar, D. Dey, J. Shah, E. Horvitz. Discovering Blind Spots in Reinforcement Learning, AAMAS 2018.
  
  
• S. Singla, B. Nushi, S. Shah, E. Kamar, E. Horvitz. Understanding Failures of Deep Networks via Robust Feature Extraction, CVPR 2021.
  
  
• B. Nushi, E. Kamar, E. Horvitz. Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure, HCOMP 2018.
  
  
• A. Segal, Y. Gal, E. Kamar, E. Horvitz, G. Miller. Optimizing Interventions via Offline Policy Evaluation: Studies in Citizen Science, AAAI 2018.
  
  
• T. Althoff, E. Horvitz, R.W. White. Psychomotor Function Measured via Online Activity Predicts Motor Vehicle Fatality Risk, Nature Digital Medicine, January 2018. doi:10.1038/s41746-017-0003-3
  
  
• H. Lakkaraju, E. Kamar, R. Caruana, E. Horvitz. Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration, AAAI 2017.
  
  
• B. Nushi, E. Kamar, E. Horvitz, D. Kossmann. On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems, AAAI 2017.
  
  
• T. Althoff, E. Horvitz, R.W. White, J. Zeitzer, Population-Scale Study of Sleep and Performance, World Wide Web Conference (WWW 2017). April 2017.
  
  
• R.W. White, P. Murali Doraiswamy, and E. Horvitz. Detecting Neurodegenerative Disorders from Web Search Signals. Nature Digital Medicine. 2018.
  
  
• S. Doroudi, E. Kamar, E. Brunskill, E. Horvitz. Toward a Learning Science for Complex Crowdsourcing Tasks. In Proceedings of CHI 2016.
  
  
• E. Fast and E. Horvitz. Identifying Dogmatism in Social Media: Signals and Models, Empirical Methods in Natural Language Processing 2016 (EMNLP), Austin TX, November 2016.
  
  
• D. Graus, P.N. Bennett, R.W. White, E. Horvitz. Analyzing and Predicting Task Reminders, 24th Annual Conference on User Modeling, Adaptation and Personalization (UMAP 2016), July 2016.
  
  
• A. Segal Y. Gal, E. Kamar, E. Horvitz, A. Bowyer, G. Miller. Intervention Strategies for Increasing Engagement in Crowdsourcing: Platform, Predictions, and Experiments, IJCAI 16, July 2016.
  
  
• D. Shahaf, E. Horvitz, R. Mankoff. Inside Jokes: Identifying Humorous Cartoon Captions. In Proceedings of KDD 2015.
  
  
• E. Kamar, A. Kapoor, E. Horvitz. Identifying and Accounting for Task-Dependent Bias in Crowdsourcing. In Proceedings of HCOMP 2015, Conference on Human Computation and Crowdsourcing, November 2015.
  
  
• E. Kamar and E. Horvitz. Planning for Crowdsourcing Hierarchical Tasks. In Proceedings of AAMAS 2015.
  
  
• A. Singla, E. Horvitz, P. Kohli, R.W. White, A Krause. Information Gathering in Networks via Active Exploration. In Proceedings of IJCAI 2015.
  
  
• Ryen W. White and Eric Horvitz. Belief Dynamics and Biases in Web Search. ACM Transactions on Information Systems (ACM TOIS), 33(4), May 2015.
  
  
• C.H. Lin, E. Kamar, E. Horvitz. Signals in the Silence: Models of Implicit Feedback in a Recommendation System for Crowdsourcing, AAAI, July 2014.
  
  
• S. Jegelka, A. Kapoor, and E. Horvitz. An Interactive Approach to Solving Correspondence Problems, International Journal of Computer Vision, Special Issue on Active and Interactive Methods in Computer Vision, 2013.
  
  
• A. Mao, E. Kamar, and E. Horvitz. Why Stop Now? Predicting Worker Engagement in Online Crowdsourcing, HCOMP 2013, Palm Springs, CA, November 2013.
  
  
• A. Mao, E. Kamar, Y. Chen, E. Horvitz, M. E. Schwamb, C.J. Lintott, and A.M. Smith. Volunteering vs. Work for Pay: Incentives and Tradeoffs in Crowdsourcing, HCOMP 2013, Palm Springs, CA, November 2013.
  
  
• E. Kamar, A. Kapoor, and E. Horvitz. Lifelong Learning for Acquiring the Wisdom of the Crowd, IJCAI 2013, Beijing, China, August 2013.
  
  
• H. Zhang, E. Horvitz, D. Parkes. Automated Workflow Synthesis, AAAI 2013, Bellevue, Washington, July 2013.
  
  
• A. Sadilek, J. Krumm, and E. Horvitz. Crowdphysics: Planned and Opportunistic Crowdsourcing for Physical Tasks, ICWSM 2013, Boston, MA, July 2013. Presentation at MIT Conference on Digital Experimentation (CODE 2014).
  
  
• E. Kamar and E. Horvitz. Light at the End of the Tunnel: A Monte Carlo Approach to Computing Value of Information, AAMAS 2013, St. Paul, Minnesota, May 2013.
  
  
• H. Zhang, E. Horvitz, R.C. Miller, and D.C. Parkes, Crowdsourcing General Computation Workshop on Crowdsourcing and Human Computation: Systems, Studies, and Platforms, ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Vancouver BC, May 2011.
  
  
• H. Zhang, E. Horvitz Y. Chen, and D. Parkes. Task Routing for Prediction Tasks, AAMAS 2012, Valencia, Spain, June 2012.
  
  
• H. Zhang, E. Horvitz, Y. Chen, and D.C. Parkes, Task Routing for Prediction Tasks Workshop on Social Computing and User-Generated Content, EC 2011: 12th ACM Conference on Electronic Commerce , San Jose, June 2011.
  
  
• E. Kamar and E. Horvitz. Light at the End of the Tunnel: A Monte Carlo Approach to Computing Value of Information, AAMAS 2013, St. Paul, Minnesota, May 2013.
  
  
• X. Chen, P.N. Bennett, K. Collins-Thompson, E. Horvitz. Pairwise Ranking Aggregation in a Crowdsourced Setting, WSDM 2013, Rome, February 2013.
  
  
• E. Kamar, S. Hacker, E. Horvitz. Combining Human and Machine Intelligence in Large-scale Crowdsourcing, AAMAS 2012, Valencia, Spain, June 2012.
  
  
• D. Shahaf and E. Horvitz. Generalized Task Markets for Human and Machine Computation, AAAI 2010, Atlanta, GA, July 2010.
  
  
• E. Kamar and E. Horvitz. Incentives for Truthful Reporting in Crowdsourcing, AAMAS 2012, Valencia, Spain, June 2012.
  
  
• W. Wang, D. Bohus, E. Kamar, E. Horvitz. Crowdsourcing the Acquisition of Natural Language Corpora: Methods and Observations, SLT 2012 - IEEE Spoken Language Technologies, Miami, FA, December 2012.
  
  
• A. Kapoor, B. Lee, D. Tan, E. Horvitz. Learning to Learn: Algorithmic Inspirations from Human Problem Solving, AAAI 2012, Toronto, July 2012.
  
  
• M. Bernstein, J. Teevan, S.T. Dumais, D. Liebling, and E. Horvitz. Direct answers for search queries in the long tail. Proceedings of CHI 2012, Austin,TX, April 2012.
  
  
• H. Zhang, E. Law, K. Gajos, R. Miller, D. Parkes, and E. Horvitz. Human Computation Tasks with Global Constraints, CHI 2012, Austin, TX, May 2012.
  
  
• E. Law, P.N. Bennett, and E. Horvitz. The Effects of Choice in Routing Relevance Judgments, SIGIR 2011, Beijing, China, July 2011.
  
  
• E. Kamar and E. Horvitz. Collaboration and Shared Plans in the Open World: Studies of Ridesharing, IJCAI 2009, Pasadena, CA, July 2009.
  
  
• M. Bernstein, D. Tan, G. Smith, M. Czerwinski, E. Horvitz. Personalization via Friendsourcing, ACM TOCHI, May 2010.
  
  
• B. Bailey, E. Horvitz. What s Your Idea? A Case Study of a Grassroots Innovation Pipeline within a Large Software Company, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Atlanta, GA, April 2010.
  
  

Search, retrieval, social media and data

• J. Suh, E. Horvitz, R.W. White, T. Althoff, Disparate impacts on online information access during the Covid-19 pandemic, Nature Communications, volume 13, Article number: 7094, 2022. (pdf)
  
  
• J. Suh, E. Horvitz, R.W. White, T. Althoff, Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications, WSDM 2021.
  
  
• K. Gligoric, R.W. White, E. Kiciman, E. Horvitz, A. Chiolero, R. West. Formation of Social Ties Influences Food Choice: A Campus-Wide Longitudinal Study, CSCW 2021.
  
  
• Y. Azar, E. Horvitz, E. Lubetzky, Y. Peres, D. Shahaf. Tractable near-optimal policies for crawling, PNAS 2018. (pdf)
  
  
• A. Spangher, G. Ranade, B. Nushi, A. Fourney, E. Horvitz. Characterizing Search-Engine Traffic to Internet Research Agency Web Properties, Web Conference 2020.
  
  
• R.W. White, P. Murali Doraiswamy, and E. Horvitz. Detecting Neurodegenerative Disorders from Web Search Signals. Nature Digital Medicine, April 2018.
  
  
• J. Zhang, J.W. Pennebaker, S.T. Dumais, E. Horvitz. Configuring Audiences: A Case Study of Email Communication. CSCW 2020.
  
  
• T. Althoff, E. Horvitz, R.W. White. Psychomotor Function Measured via Online Activity Predicts Motor Vehicle Fatality Risk, Nature Digital Medicine, January 2018. doi:10.1038/s41746-017-0003-3
  
  
• R. Boyd, A. Spangher, A. Fourney, B. Nushi, G. Ranade, J. Pennebaker, E. Horvitz. Characterizing the Internet Research Agency's Social Media Operations During the 2016 U.S. Presidential Election using Linguistic Analyses, PsyArXiv Preprints 2018. doi: 10.31234/osf.io/ajh2q
  
  
• T. Althoff, E. Horvitz, R.W. White, J. Zeitzer, Population-Scale Study of Sleep and Performance, World Wide Web Conference (WWW 2017). April 2017.
  
  
• E. Horvitz and R.W. White, Editorial: Making Connections: Advancing Healthcare Research via Consumer Mobile Devices. Circulation: Cardiovascular Quality and Outcomes. 2017;10:e003573 (web version)
  
  
• E. Fast and E. Horvitz. Identifying Dogmatism in Social Media: Signals and Models, Empirical Methods in Natural Language Processing 2016 (EMNLP), Austin TX, November 2016.
  
  
• R. W. White and E. Horvitz. Early Signs of Lung Carcinoma in Web Search Logs: Findings and Implications, JAMA Oncology, November 2016.
  
  
• J. Paparrizos, R.W. White, E. Horvitz. Screening for Pancreatic Adenocarcinoma using Signals from Web Search Logs: Feasibility Study and Results, Journal of Oncology Practice, June 7, 2016. doi: 10.1200/JOP.2015.010504.
  
  
• J. Paparrizos, R.W. White, E. Horvitz. Detecting Devastating Diseases in Search Logs, In Proceedings of KDD 2016.
  
  
• M.J. Paul, R.W. White, E. Horvitz. Search and Breast Cancer: On Episodic Shifts of Attention over Life Histories of an Illness, ACM Transactions on the Web (ACM TWEB), 2016. (Addendum: Breast cancer search term ontology)
  
  
• E. Horvitz and D. Mulligan. Data, privacy, and the greater good, 16 July 2015, Science 349. 253-255 (2015). (full text, reprint).
  
  
• D. Shahaf, C. Guestrin, E. Horvitz, J. Leskovec. Information Cartography, Communications of the ACM 58:11, pp. 62-73, November 2015.
  
  
• R.W. White, S. Wang, A. Pant, R. Harpaz, P. Shukla, W. Sun, W. DuMouchel, E. Horvitz. Early Identification of Adverse Drug Reactions from Search Log Data, Journal of Biomedical Informatics. 59:42 48, 2015.
  
  
• J. Krumm and E. Horvitz. Eyewitness: Identifying Local Events via Space-Time Signals in Twitter Feeds. In Proceedings of SIGSpatial 2015.
  
  
• D. Shahaf, E. Horvitz, R. Mankoff. Inside Jokes: Identifying Humorous Cartoon Captions. In Proceedings of KDD 2015.
  
  
• R.W. White and E. Horvitz. Belief Dynamics and Biases in Web Search. ACM Transactions on Information Systems (ACM TOIS), 33(4), May 2015.
  
  
• M.J. Paul, R.W. White, E. Horvitz. Diagnoses, Decisions, and Outcomes: Web Search as Decision Support for Cancer. In Proceedings of WWW 2015.
  
  
• D. Koutra, P.N. Bennett, E. Horvitz. Events and Controversies: Influences of a Shocking News Event on Information Seeking. In Proceedings of WWW 2015.
  
  
• A. Fourney, R.W. White, E. Horvitz. Exploring Time-Dependent Concerns about Pregnancy and Childbirth from Search Logs. In Proceedings of CHI 2015.
  
  
• J. Leskovec and E. Horvitz. Geospatial Structure of a Planetary-Scale Social Network. IEEE Transactions on Computational Social Systems, December 2014.
  
  
• R.W. White, R. Harpaz, N.H. Shah, W. DuMouchel, and E. Horvitz. Toward Enhanced Pharmacovigilance using Patient-Generated Data on the Internet, Nature CPT, April 2014.
  
  
• A. Singla, E. Horvitz, E. Kamar, R.W. White. Stochastic Privacy, AAAI, July 2014.
  
  
• N. Mishra, R. W. White, S. Ieong, E. Horvitz. Time-Critical Search, SIGIR 2014, July 2014.
  
  
• R.W. White, A. Hassan, A. Singla, and E. Horvitz. From Devices to People: Attribution of Search Activity in Multi-User Settings, WWW 2014, Seoul, April, 2014.
  
  
• R.W. White, N.P. Tatonetti, N. H. Shah, R.B. Altman, E. Horvitz. Web-Scale Pharmacovigilance: Listening to Signals from the Crowd. JAMIA, March 2013.
  
  
• M. De Choudhury, S. Counts, E. Horvitz, A. Hoff. Characterizing and Predicting Postpartum Depression from Facebook Data., ICWSM 2014, Baltimore, MD, February 2014.
  
  
• S. Yang, R. White, E. Horvitz. Pursuing Insights about Healthcare Utilization via Geocoded Search Queries, SIGIR 2013, Dublin, Ireland, July 2013.
  
  
• R. West, R. White, E. Horvitz. Here and There: Goals, Activities, and Predictions about Location from Geotagged Queries, SIGIR 2013, Dublin, Ireland, July 2013.
  
  
• E. Yom-Tov, R. W. White, E. Horvitz. Seeking Insights about Cycling Disorders via Anonymized Search Logs, Journal of Medical Internet Research, 2014 16(2):e65.
  
  
• M. De Choudhury, M. Gamon, S. Counts, E. Horvitz. Predicting Depression via Social Media, ICWSM 2013, Boston, MA, July 2013.
  
  
• M. De Choudhury, S. Counts, E. Horvitz. Social Media as a Measurement Tool of Depression in Populations, WebSci 2013, May 2013, Paris, France.
  
  
• M. De Choudhury, S. Counts, E. Horvitz. Predicting Postpartum Changes in Emotion and Behavior via Social Media, CHI 2013, April 2013, Paris, France.
  
  
• M. De Choudhury, S. Counts, E. Horvitz. Major Life Changes and Behavioral Markers in Social Media: Case of Childbirth, CSCW 2013, February 2013, San Antonio, Texas.
  
  
• R. West, R.W. White, E. Horvitz, From Cookies to Cooks: Insights on Dietary Patterns via Analysis of Web Usage Logs, WWW 2013, Rio de Janeiro, Brazil, May 2013.
  
  
• Ryen W. White and E. Horvitz. Captions and Biases in Diagnostic Search, ACM Transactions on the Web (ACM TWEB), 2013.
  
  
• Ryen W. White and E. Horvitz. From Health Search to Health Care: Explorations of Intention and Utilization via Query Logs and User Surveys, Journal of the American Medical Informatics Association (JAMIA), May 2013.
  
  
• K. Radinsky and E. Horvitz. Mining the Web to Predict Future Events, WSDM 2013, Rome, February 2013.
  
  
• D. Shahaf, C. Guestrin, E. Horvitz. Metro Maps for Science, KDD 2012, August 2012, Beijing, China.
  
  
• K. Radinsky, K. Svore, S. Dumais, J. Teevan, A. Bocharov, E. Horvitz. Modeling and Predicting Behavioral Dynamics on the Web, WWW 2012, Lyon, France, April 2012.
  
  
• D. Shahaf, C. Guestrin, E. Horvitz. Trains of Thought: Generating Information Maps, WWW 2012, Lyon, France, April 2012.
  
  
• M. Bernstein, J. Teevan, S.T. Dumais, D. Liebling, and E. Horvitz. Direct answers for search queries in the long tail. Proceedings of CHI 2012, Austin,TX, April 2012.
  
  
• A. Krause and E. Horvitz. A Utility-theoretic Approach to Privacy in Online Services, Journal of Artificial Intelligence Research, 39 (2010) 633-662.
  
  
• R. White and E. Horvitz. Studies of the Onset and Persistence of Medical Concerns in Search Logs, SIGIR 2012, Portland, OR, August 2012.
  
  
• R.W. White and E. Horvitz. From Web Search to Healthcare Utilization: Privacy-Sensitive Studies from Mobile Data, JAMIA: Journal of the American Medical Informatics Association, June 2012, doi:10.1136/amiajnl-2011-000765.
  
  
• E. Law, P.N. Bennett, and E. Horvitz. The Effects of Choice in Routing Relevance Judgments, SIGIR 2011, Beijing, China, July 2011.
  
  
• M. Cartright, R.W. White, and E. Horvitz. Intentions and Attention in Exploratory Health Search, SIGIR 2011, Beijing, China, July 2011.
  
  
• R. White and E. Horvitz. Predicting Escalations of Medical Queries Based on Web Page Structure and Content, SIGIR 2010, Geneva, Switzerland, July 2010.
  
  
• A. Kapoor, N. Eagle, E. Horvitz. People, Quakes, and Communications: Inferences from Call Dynamics about a Seismic Event and its Influences on a Population. Proceedings of AAAI Symposium on Artificial Intelligence for Development, Stanford CA, March 2010.
  
  
• J. Teevan, S.T. Dumais, E. Horvitz. Potential for Personalization, ACM Transactions on Computer-Human Interaction, March 2010.
  
  
• R. White and E. Horvitz. Web to World: Predicting Transitions from Self-Diagnosis to the Pursuit of Local Medical Assistance in Web Search, AMIA 2010, Washington DC, November 2010.
  
  
• R.W. White and E. Horvitz. Experiences with Web Search on Medical Concerns and Self Diagnosis. Proceedings of AMIA 2009. San Francisco, CA, November 2009.
  
  
• D. Downey, S. Dumais, D. Leibling, E. Horvitz. Understanding the Relationship between Searchers Queries and Information Goals, Proceedings of CIKM 2008, 17th Conference on Information and Knowledge Management, Napa, California, October 2008.
  
  
• R.W. White and E. Horvitz. Cyberchondria: Studies of the Escalation of Medical Concerns in Web Search. ACM Transactions on Information Systems, 27(4), Article 23, November 2009, DOI 101145/1629096.1629101. Also Microsoft Research Technical Report MSR-TR-2008-178, November 2008.
  
  
• J. Leskovec, S. Dumais, E. Horvitz. Web Projections: Learning from Contextual Subgraphs of the Web, Proceedings of World Wide Web 2007, Banff, Canada, May 2007.
  
  
• D. Downey, S. Dumais, and E. Horvitz. Models of Searching and Browsing: Languages, Studies, and Applications, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, January 2007.
  
  
• D. Downey, S. Dumais, and E. Horvitz. Heads and Tails: Studies of Web Search with Common and Rare Queries, Proceedings of SIGIR 2007, ACM Press, August 2007.
  
  
• J. Teevan, S. Dumais, and E. Horvitz. Characterizing the Value of Personalizing Search, Proceedings of SIGIR 2007, ACM Press, August 2007.
  
  
• J. Teevan, S. T. Dumais, and E. Horvitz, Personalizing Search via Automated Analysis of Interests and Activities, Proceedings of SIGIR 2005, ACM Press, August 2005.
  
  
• J. Teevan, S.T. Dumais and E. Horvitz. Beyond the Commons: Investigating the Value of Personalizing Web Search. Proceedings of Workshop on New Technologies for Personalized Information Access (PIA '05), Edinburgh, Scotland, UK, July 2005.
  
  
• E. Gabrilovich, S. Dumais, E. Horvitz, Newsjunkie: Providing Personalized Newsfeeds via Analysis of Information Novelty, Proceedings of the Thirteenth International World Wide Web Conference (WWW 2004), May 2004, New York, pp. 482-490.
  
  
• X. Shen, S. Dumais, E. Horvitz, Analysis of Topic Dynamics in Web Search, Proceedings of the Fourteenth International World Wide Web Conference(WWW 2005), May 2005.
  
  
• Susan Dumais, Edward Cutrell, Raman Sarin, Eric Horvitz. Implicit queries (IQ) for contextualized search, Proceedings of the 27th annual international conference on Research and development in information retrieval, August 2004.
  
  
• D. Azari, E. Horvitz, S. Dumais, E. Brill. Actions, Answers, and Uncertainty: A Decision Making Perspective on Web-Based Question Asking , Information Processing and Management, 40(5), 2004, pp. 849-868.
  
  
• E. Horvitz, S. Dumais, P. Koch. Learning Predictive Models of Memory Landmarks, CogSci 2004: 26th Annual Meeting of the Cognitive Science Society, Chicago, August 2004.
  
  
• E. Horvitz, A Curse of Riches or a Blessing? Information Access and Awareness under Scarce Cognitive Resources, Keynote abstract, Adaptive Hypermedia 2004, Eindhoven, Netherlands, August 2004.
  
  
• P. N. Bennett, S. T. Dumais, E. Horvitz. Inductive Transfer for Text Classification using Generalized Reliability Indicators, Proceedings of the ICML-2003 Workshop on The Continuum from Labeled to Unlabeled Data, Washington DC, August 2003.
  
  
• D. Azari, E. Horvitz, S. Dumais, E. Brill. A Decision Making Perspective on Web Question Answering, Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence, Acapulco, Mexico, August 2003.
  
  
• P. N. Bennett, S. T. Dumais, and E. Horvitz. The Combination of Text Classifiers using Reliability Indicators. Information Retrieval.
  
  
• P. N. Bennett, S. T. Dumais, and E. Horvitz. Probabilistic Combination of Text Classifiers Using Reliability Indicators: Models and Results. In: Proceedings of 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Tampere, Finland, August 2002.
  
  
• C. R. Anderson and E. Horvitz. Web Montage: A Dynamic Personalized Start Page, Eleventh Inernational World Wide Web Conference, Honolulu, Hawaii, May 2002.
  
  
• I. Zukerman and E. Horvitz. Using Machine Learning Techniques to Interpret WH-questions. Proceedings of Association for Computational Linguistics (ACL-2001), Toulouse, France, July 2001.
  
  
• I. Zukerman and E. Horvitz, Toward Understanding WH-Questions: A Statistical Analysis. Workshop on Machine Learning, Information Retrieval, and User Modeling, Sonthofen, Germany, July 2001.
  
  
• T. Lau and E. Horvitz, Patterns of Search: Analyzing and Modeling Web Query Refinement. Proceedings of the Seventh International Conference on User Modeling, Banff, Canada, June 1999. New York: Springer Wien.
  
  
• D. Heckerman and E. Horvitz. Inferring Informational Goals from Free-Text Queries. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July 1998, Morgan Kaufmann: San Francisco, pp. 230-237.

Biomedical informatics

• H. Nori, Y. Lee, S. Zhang, D.Carignan, R. Edgar, N. Fusi, N. King, J. Larson, Y. Li, W. Liu, R. Luo, S. Mayer McKinney, R.O. Ness, H. Poon, T. Qin, N. Usuyama, C. White, and E. Horvitz, Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine, arXiv eprint: 2311.16452, November 27, 2023.
  
  
• H. Nori, N. King, S. Mayer McKinney, D. Carignan, E. Horvitz, Capabilities of GPT-4 on Medical Challenge Problems, arXiv preprint 2303.13375, March 20, 2023.
  
  
• U. Singer, K. Radinsky, E. Horvitz. On Biases of Attention in Scientific Discovery, Journal of Bioinformatics, December 2020. At J. Bioinformatics.
  
  
• S. Agmon, P. Gillis, E. Horvitz, K. Radinsky. Gender-sensitive word embeddings for healthcare, Journal of the American Medical Informatics Association, December 2021.
  
  
• D.H. Lee, M. Yetisgen, L. Vanderwende, E. Horvitz. Predicting Severe Clinical Events by Learning about Life-Saving Actions and Outcomes using Distant Supervision, Journal of Biomedical Informatics 2020.
  
  
• K. Gligoric, R.W. White, E. Kiciman, E. Horvitz, A. Chiolero, R. West. Formation of Social Ties Influences Food Choice: A Campus-Wide Longitudinal Study, CSCW 2021.
  
  
• E. Horvitz. AI, Biomedicine, and Pandemics: Directions and Opportunities, Position Statement, IJCAI 2020 Panel on AI Approaches for COVID-19 and Future Pandemics, IJCAI 2020, January 2021.
  
  
• R. W. White and E. Horvitz. Population-Scale Hand Tremor Analysis via Anonymized Mouse Cursor Signals. NPG Digital Medicine, Vol. 2, Article 93, 5(4) 2019.
  
  
• D.H. Lee, M. Yetisgen, E. Horvitz. Toward an Early Warning System on Need for Lifesaving Interventions in Intensive Care Patients, Critical Care Medicine, 2018.
  
  
• R.W. White, P. Murali Doraiswamy, and E. Horvitz. Detecting Neurodegenerative Disorders from Web Search Signals. Nature Digital Medicine, April 2018.
  
  
• E. Horvitz, The Future of Biomedical Informatics: Bottlenecks and Opportunities, In: E.H. Shortliffe, J.J. Cimino, et. al, Biomedical Informatics: Computer Applications in Health Care and Biomedicine, Springer, 2021.
  
  
• T. Althoff, E. Horvitz, R.W. White. Psychomotor Function Measured via Online Activity Predicts Motor Vehicle Fatality Risk, Nature Digital Medicine, January 2018. doi:10.1038/s41746-017-0003-3
  
  
• R. Harpaz, W. DuMouchel, M. Schuemieb, O. Bodenreiderc, C. Friedmand, E. Horvitz, A. Ripple, A. Sorbellof, R.W. White, R. Winnenburgg, N.H. Shah. Toward multimodal signal detection of adverse drug reactions, Journal of Biomedical Informatics 76 (2017) 41 49.
  
  
• J. Wiens, J. Guttag, and E. Horvitz. Patient Risk Stratification with Time-Varying Parameters: A Multitask Learning Approach. Journal of Machine Learning Research (JMLR), April 2016.
  
  
• R. W. White and E. Horvitz. Early Signs of Lung Carcinoma in Web Search Logs: Findings and Implications, JAMA Oncology, November 2016.
  
  
• T. Althoff, E. Horvitz, R.W. White, J. Zeitzer, Population-Scale Study of Sleep and Performance, World Wide Web Conference (WWW 2017). April 2017.
  
  
• E. Horvitz and R.W. White, Editorial: Making Connections: Advancing Healthcare Research via Consumer Mobile Devices. Circulation: Cardiovascular Quality and Outcomes. 2017;10:e003573 (web version)
  
  
• T. Althoff, R.W. White, E. Horvitz. Influence of Pok mon Go on Physical Activity: Study and Implications, Journal of Medical Internet Research, 2017 (in press).
  
  
• J. Paparrizos, R.W. White, E. Horvitz. Detecting Devastating Diseases in Search Logs, In Proceedings of KDD 2016.
  
  
• J. Paparrizos, R.W. White, E. Horvitz. Screening for Pancreatic Adenocarcinoma using Signals from Web Search Logs: Feasibility Study and Results, Journal of Oncology Practice, June 7, 2016. doi: 10.1200/JOP.2015.010504.
  
  
• E. P. Frady, A. Kapoor, E. Horvitz, W.B. Kristan. Scalable Semisupervised Functional Neurocartography Reveals Canonical Neurons in Behavioral Networks, Neural Computation, June 2016. doi:10.1162/NECO_a_00852.
  
  
• M.J. Paul, R.W. White, E. Horvitz. Search and Breast Cancer: On Episodic Shifts of Attention over Life Histories of an Illness, ACM Transactions on the Web (ACM TWEB), 2016. (Addendum: Breast cancer search term ontology)
  
  
• R.W. White, S. Wang, A. Pant, R. Harpaz, P. Shukla, W. Sun, W. DuMouchel, E. Horvitz. Early Identification of Adverse Drug Reactions from Search Log Data, Journal of Biomedical Informatics. 59:42 48, 2015.
  
  
• M. Bayati, M. Braverman, M. Gillam, K.M. Mack, G. Ruiz, M.S. Smith, E. Horvitz. Data-Driven Decisions for Reducing Readmissions for Heart Failure: General Methodology and Case Study. PLOS One Medicine. October 2014.
  
  
• J. Wiens, Wayne N. Campbell, Ella S. Franklin, J. Guttag, E. Horvitz. Learning Data-Driven Patient Risk Stratification Models for Clostridium difficile. Open Forum Infectious Diseases Advance Access, June 2014.
  
  
• J. Wiens, J. Guttag, and E. Horvitz. A Study in Transfer Learning: Leveraging Data from Multiple Hospitals to Enhance Hospital-Specific Predictions, Journal of the American Medical Informatics Association: 0:1 8, January 2014.
  
  
• M.J. Paul, R.W. White, E. Horvitz. Diagnoses, Decisions, and Outcomes: Web Search as Decision Support for Cancer. In Proceedings of WWW 2015.
  
  
• R. Harpaz, D. Odgers, G. Gaskin, N.H. Shah, W. DuMouchel, R. Winnenburg, O. Bodenreider, A. Ripple, A. Szarfman, A. Sorbello, E. Horvitz, R. W. White, N.H. Shah. A time-indexed reference standard of adverse drug reactions, Nature Scientific Data, November 2014.
  
  
• J. Wiens, J. Guttag, E. Horvitz. Patient Risk Stratification for Hospital-Associated C. Diff as a Time-Series Classification Task, NIPS 2012, Lake Tahole, CA, December 2012.
  
  
• R.W. White, R. Harpaz, N.H. Shah, W. DuMouchel, and E. Horvitz. Toward Enhanced Pharmacovigilance using Patient-Generated Data on the Internet, Nature CPT, April 2014.
  
  
• R.W. White, N.P. Tatonetti, N. H. Shah, R.B. Altman, E. Horvitz. Web-Scale Pharmacovigilance: Listening to Signals from the Crowd. JAMIA, March 2013.
  
  
• J. Wiens, J. Guttag, E. Horvitz. Learning Evolving Patient Risk Processes for C. Diff Colonization, Machine Learning for Clinical Data Analysis, ICML 2012, Edinburgh, Scotland, June 2012.
  
  
• R. White and E. Horvitz. Studies of the Onset and Persistence of Medical Concerns in Search Logs, SIGIR 2012, Portland, OR, August 2012.
  
  
• R. West, R.W. White, E. Horvitz, From Cookies to Cooks: Insights on Dietary Patterns via Analysis of Web Usage Logs, WWW 2013, Rio de Janeiro, Brazil, May 2013.
  
  
• Ryen W. White and E. Horvitz. Captions and Biases in Diagnostic Search, ACM Transactions on the Web (ACM TWEB), 2013.
  
  
• Ryen W. White and E. Horvitz. From Health Search to Health Care: Explorations of Intention and Utilization via Query Logs and User Surveys, Journal of the American Medical Informatics Association (JAMIA), May 2013.
  
  
• S. Yang, R. White, E. Horvitz. Pursuing Insights about Healthcare Utilization via Geocoded Search Queries, SIGIR 2013, Dublin, Ireland, July 2013.
  
  
• R.W. White and E. Horvitz. From Web Search to Healthcare Utilization: Privacy-Sensitive Studies from Mobile Data, JAMIA: Journal of the American Medical Informatics Association, June 2012, doi:10.1136/amiajnl-2011-000765.
  
  
• M. Cartright, R.W. White, and E. Horvitz. Intentions and Attention in Exploratory Health Search, SIGIR 2011, Beijing, China, July 2011.
  
  
• R. White and E. Horvitz. Predicting Escalations of Medical Queries Based on Web Page Structure and Content, SIGIR 2010, Geneva, Switzerland, July 2010.
  
  
• R. White and E. Horvitz. Web to World: Predicting Transitions from Self-Diagnosis to the Pursuit of Local Medical Assistance in Web Search, AMIA 2010, Washington DC, November 2010.
  
  
• L.G. Wilcox, D. Morris, D. Tan, J. Gatewood, E. Horvitz, Characterizing Patient-Friendly Micro-Explanations of Medical Events, Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), Vancouver BC, May 2011.
  
  
• L.G. Wilcox, J. Gatewood, D. Morris, D.S. Tan, S. Feiner, E. Horvitz. Physician Attitudes about Patient-Facing Information Displays at an Urban Emergency Department, AMIA 2010, Washington DC, November 2010.
  
  
• J. Benaloh, M. Chase, E. Horvitz, K. Lauter. Patient Controlled Encryption: Ensuring Privacy in Electronic Medical Records, ACM CCSW 2009, Chicago, IL, November, 2009.
  
  
• E. Horvitz. From Data to Predictions and Decisions: Enabling Evidence-Based Healthcare, Data Analytic Series, Computing Community Consortium, Computing Research Association (CRA), September 2010. Also, Microsoft Research Technical Report MSR-TR-2010-152, September 2010.
  
  
• S. Graham, D. Estrin, E. Horvitz, I. Kohane, E. Mynatt, I. Sim. Information Technology Research Challenges for Healthcare: From Discovery to Delivery, Computing Community Consortium Whitepaper Series, Computing Research Association (CRA), May 2010.
  
  
• R.W. White and E. Horvitz. Experiences with Web Search on Medical Concerns and Self Diagnosis. Proceedings of AMIA 2009. San Francisco, CA, November 2009.
  
  
• R.W. White and E. Horvitz. Cyberchondria: Studies of the Escalation of Medical Concerns in Web Search. ACM Transactions on Information Systems, 27(4), Article 23, November 2009, DOI 101145/1629096.1629101. Also Microsoft Research Technical Report MSR-TR-2008-178, November 2008.
  
  
• E. Horvitz and A. Seiver. Time-Critical Action: Representations and Application. Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, August 1997.
  
  
• E. Horvitz. Advanced Information Technologies of the Future. Critical Care Symposium 1999: Proceedings of the 28th Educational & Scientific Symposium of the Society for Critical Care Medicine, January 1999, pp. 331-333.
  
  
• E. Horvitz and M. Shwe, Handsfree Decision Support: Toward a Non-invasive Human-Computer Interface, Nineteenth Annual Symposium on Computer Applications in Medical Care. Toward Cost-Effective Clinical Computing, November 1995. View photo and videos of early prototype.
  
  
• E. Horvitz, Automated Reasoning for Biology and Medicine, In R. Fortuner, ed., Advances in Computer Methods for Systematic Biology: Artificial Intelligence, Databases, and Computer Vision, Johns Hopkins University Press: Baltimore, 1993.
  
  
• E. Horvitz. Innovations at the Human Computer Interface: A Medical-Informatics Perspective, In Proceedings of MMVR I, Medicine Meets Virtual Reality I, San Diego, June 1992.
  
  
• E. Horvitz and G. Rutledge. Time-Dependent Utility and Action Under Uncertainty. Uncertainty in Artificial Intelligence, Los Angeles, pp. 151-158. Morgan Kaufman, 1991 (pdf).
  
  
• D. Heckerman and E. Horvitz. Problem Formulation as the Reduction of a Decision Problem. Proceedings of the Conference on Uncertainty in Artificial Intelligence, Cambridge, MA July 1990, Association for Uncertainty and Artificial Intelligence, pp. 82-89.
  
  
• E. Horvitz, D. Heckerman, K. Ng, B. Nathwani, Heuristic Abstraction in the Decision-Theoretic Pathfinder System, Symposium on Computer Applications in Medical Care, Washington DC, IEEE Press: Silver Springs, MD, November 1989.
  
  
• D. Heckerman, E. Horvitz, and B. Nathwani. Update on the Pathfinder project, Symposium on Computer Applications in Medical Care, Washington DC, IEEE Press: Silver Springs, MD, November 1989.
  
  
• B.N. Nathwani, D.E. Heckerman, E.J. Horvitz, T.L. Lincoln. Integrated expert systems and videodisc in surgical pathology: An overview. Human Pathology 1990, 21:11-27.
  
  
• D. E. Heckerman, E. J. Horvitz, and B. N. Nathwani. Toward Normative Expert Systems: Part I The Pathfinder Project. Methods of Information in Medicine, 31:90-105, 1992 (pdf).
  
  
• M. Henrion, J. Breese, and E. J. Horvitz. Decision Analysis and Expert Systems, AI Magazine 12(4), Winter 1991, pp 64-91.
  
  
• M.A. Shwe, B. Middleton, D.E. Heckerman, M. Henrion, F.J. Horvitz, H.P.Lehmann, and G.E. Cooper. Probabilistic Diagnosis Using a Reformulation of the Internist-1/QMR Knowledge Base. I. The probabilistic Model and Inference Algorithms. Methods of Information in Medicine, Vol. 30, pp. 241-255, 1991. (pdf). Also in, Stanford University Computer Science Department Technical Report KSL-90-09, 1990.
  
  
• B. Middleton, M.A. Shwe, D.E. Heckerman, M. Henrion, E.J.Horvitz, H.P. Lehmann, and G.E. Cooper. Probabilistic Diagnosis Using a Reformulation of the Internist-1/QMR Knowledge Base. II. Evaluation of Diagnostic Performance. Methods of Information in Medicine, Vol. 30, pp. 256-267, 1991 (pdf). Also, Stanford University Computer Science Department Technical Report KSL-90-68, 1990. Download report.
  
  
• E.J. Horvitz, Toward a Science of Expert Systems, In: Proceedings of the 18th Symposium on the Interface of Statistics and Computer Science, Fort Collins, Colorado, March 1986, Thomas J. Boardman, Editor, American Statistical Association: Washington, D.C., pp. 45-52 (pdf).
  
  LI> E. Horvitz, D. Heckerman, B. Nathwani, L.M. Fagan, The use of a heuristic problem-solving hierarchy to facilitate the explanation of hypothesis-directed reasoning, October 1986, In: Proceedings of Medinfo, Washington, DC, North Holland: New York, pp. 27-31 (pdf).
  
  
• E.J. Horvitz, D.E. Heckerman, B.N. Nathwani, L.M. Fagan, Diagnostic Strategies in the Hypothesis-Directed Pathfinder System, In: Proceedings of the First Conference on Artificial Intelligence Applications, Denver, Colorado, December 1984. IEEE Computer Society, Computer Society Press, pp. 630-636 (pdf).
  

Privacy

• E. Horvitz and D. Mulligan. Data, privacy, and the greater good, 16 July 2015, Science 349. 253-255 (2015).
  
  
• E. Horvitz, M. Clyburn, E. Felten, T. LeBlanc, Caution Ahead: Navigating Risks to Freedoms Posed by AI. The Hill, May 17, 2021.
  
  
• H. Aly, J. Krumm, G. Ranade, E. Horvitz. Computing Value of Spatiotemporal Information, CACM Research Highlight, CACM 2020.
  
  
• H. Aly, J. Krumm, G. Ranade, E. Horvitz. On the Value of Spatiotemporal Information: Principles and Scenarios, ACM SIGSPATIAL 2018.
  
  
• A. Singla, E. Horvitz, E. Kamar, R.W. White. Stochastic Privacy, AAAI, July 2014.
  
  
• A. Krause and E. Horvitz. A Utility-theoretic Approach to Privacy in Online Services, Journal of Artificial Intelligence Research, 39 (2010) 633-662.
  
  
• J. Benaloh, M. Chase, E. Horvitz, K. Lauter. Patient Controlled Encryption: Ensuring Privacy in Electronic Medical Records, ACM CCSW 2009, Chicago, IL, November, 2009.
  
  
• A. Krause, E. Horvitz, A. Kansal, F. Zhao. Toward Community Sensing, Proceedings of IPSN 2008, International Conference on Information Processing in Sensor Networks, St. Louis, Missouri, April 2008.
  
  
• A. Krause and E. Horvitz. A Utility-Theoretic Approach to Privacy and Personalization, AAAI-08: Twenty-Third Conference on Artificial Intelligence, Chicago, Illinois, July 2008.
  
  
• P. Dewan, J. Grudin, E. Horvitz. Towards Mixed-Initiative Access Control, Proceedings of the IEEE Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2007), November 2007, 64-71.
  
  
• J. Olson, J. Grudin, E. Horvitz. A Study of Preferences for Sharing and Privacy. ACM SIGCHI Conference on Human Factors in Computing Systems, Portland, OR , April, 2005.
  
  
• J. Teevan, S. T. Dumais, and E. Horvitz, Personalizing Search via Automated Analysis of Interests and Activities, Proceedings of SIGIR 2005, ACM Press, August 2005.
  
  

Technology, Policy, and Society

• E. Horvitz. AI, People, and Society, Science 07 Jul 2017: Vol. 357, Issue 6346, pp. 7. DOI: 10.1126/science.aao2466
  
  
• A. Sellen and E. Horvitz, The Rise of the AI Co-Pilot: Lessons for Design from Aviation and Beyond, arXiv eprint: 2311.14713, November 16, 2023.
  
  
• E. Horvitz, V. Conitzer, S. McIlraith, P. Stone, Now, Later, and Lasting: Ten Priorities for AI Research, Policy, and Practice, CACM 2024..
  
  
• E. Horvitz, On the Horizon: Interactive and Compositional Deepfakes, International Conference on Multimodal Interaction (ICMI), November 2022. video
  
  
• H. Nori, N. King, S. Mayer McKinney, D. Carignan, E. Horvitz, Capabilities of GPT-4 on Medical Challenge Problems, March 20, 2023.
  
  
• E. Horvitz, Reflections on AI and the Future of Human Flourishing. In: E. Horvitz (ed.), AI Anthology. https://unlocked.microsoft.com/ai-anthology/eric-horvitz, May 2023.
  
  
• E. Horvitz, ed., AI Anthology. https://unlocked.microsoft.com/ai-anthology, May 2023.
  
  
• E. Horvitz, Artificial Intelligence and Cybersecurity: Rising Challenges and Promising Directions, In: Hearing on Artificial Intelligence Applications to Operations in Cyberspace before the Subcommittee on Cybersecurity, of the Senate Armed Services Committee, 117th Congress, May 3, 2022.
  
  
• E. Horvitz, Reflections on the Status and Future of Artificial Intelligence, Testimony Before the United States Senate, Hearing on the Dawn of Artificial Intelligence, Committee on Commerce Subcommitte on Space, Science, and Competitiveness, November 30, 2016.
  
  
• E. Horvitz, M. Clyburn, J. Griffiths, J. Matheny. Privacy and Ethics Recommendations for Computing Applications Developed to Mitigate COVID-19, White Paper Series on Pandemic Response and Preparedness, No. 1, National Security Commission on AI, May 2020.
  
  
• E. Horvitz, J. Young, R.G. Elluru, C. Howell. Key Considerations for the Responsible Development and Fielding of Artificial Intelligence, National Security Commission on Artificial Intelligence (NSCAI), April 2021. Abridged version, podcast highlight
  
  
• Safra Catz, Steve Chien, Mignon Clyburn, Chris Darby, Kenneth Ford, Jos -Marie Griffiths Eric Horvitz Andrew Jassy, Gilman Louie, William Mark, Jason Matheny, Katharina McFarland, Andrew Moore, Eric Schmidt, Robert Work. Report of the National Security Commission on Artificial Intelligence, National Security Commission on Artificial Intelligence (NSCAI), March 2021.
  
  
• J. Chan, D. Foster, S. Gollakota, E. Horvitz, J. Jaeger, Sham Kakade, Tadayoshi Kohno, J. Langford, J. Larson, P. Sharma, S. Singanamalla, Jacob Sunshine, S. Tessaro. PACT: Privacy-Sensitive Protocols And Mechanisms for Mobile Contact Tracing, Bulletin of the Technical Committee on Data Engineering, 43(2), IEEE Computer Society June 2020. arXiv version
  
  
• J. Aythora, et al. Multi-stakeholder Media Provenance Management to Counter Synthetic Media Risks in News Publishing, International Broadcasting Convention 2020 (IBC 2020), Amsterdam, NL 2020. (video.)
  
  
• E. Horvitz. On Responsibilities and Ethics with the Development and Fielding of AI: Reflections and Experiences - 责任伦理与Al的发展与实践：反思与经验 Eric Horvitz博士 微软首席科学官, Panel on Ethics and Culture of Science and Technology, World Science and Technology Development Forum, Beijing, November 2020.
  
  
• P. England, H.S. Malvar, E. Horvitz, J.W. Stokes, C. Fournet, et al. AMP: Authentication of Media via Provenance, ACM Multimedia Systems 2021.
  
  
• E. Horvitz. Critical attention required on the increasing sophistication and scope of disinformation, In: Microsoft Digital Defense Report, October 2021.
  
  
• A. Spangher, G. Ranade, B. Nushi, A. Fourney, E. Horvitz. Characterizing Search-Engine Traffic to Internet Research Agency Web Properties, Web Conference 2020.
  
  
• C. Welty, L. Aroyo, E. Horvitz, The AI Bookie. AI Magazine, 40(1), March 2019, pp. 79-82. https://doi.org/10.1609/aimag.v40i1.2861
  
  
• A. Fourney, M.Z. Racz, G. Ranade, M. Mobius, E. Horvitz. Geographic and Temporal Trends in Fake News Consumption During the 2016 US Presidential Election, CIKM 2017.
  
  
• R. Boyd, A. Spangher, A. Fourney, B. Nushi, G. Ranade, J. Pennebaker, E. Horvitz. Characterizing the Internet Research Agency's Social Media Operations During the 2016 U.S. Presidential Election using Linguistic Analyses, PsyArXiv Preprints 2018. doi: 10.31234/osf.io/ajh2q
  
  
• T. Ahmad, R. Chandra, A. Kapoor, M. Daum, E. Horvitz. Wi-Fly: Widespread Opportunistic Connectivity via Commercial Air Transport, HotNets 2017: ACM Workshop on Hot Topics in Networks.
  
  
• E. Fast and E. Horvitz. Long-Term Trends in the Public Perception of Artificial Intelligence, AAAI 2017.
  
  
• E. Horvitz. Reflections On the meaningful understanding of the logic of automated decision-making (presentation), Privacy Law Forum, Berkeley Center for Law & Technology, March 2017.
  
  
• T.G. Dietterich and E.J. Horvitz, Rise of Concerns about AI: Reflections and Directions. Communications of the ACM, Vol. 58 No. 10, pages 38-40 10.1145/2770869
  
  Eric Horvitz, One-Hundred Year Study on Artificial Intelligence: Reflections and Framing, One Hundred Year Study on Artifical Intelligence, Stanford University 2014.
  
  
• E. Horvitz and D. Mulligan. Data, privacy, and the greater good, 16 July 2015, Science 349. 253-255 (2015).
  
  
• A. Howard, C. Zhang, E. Horvitz. Addressing Bias in Machine Learning Algorithms: A Pilot Study on Emotion Recognition for Intelligent Systems. IEEE Workshop on Advanced Robotics and its Social Impacts, Austin, USA on March 8-10, 2017, Austin, TX. DOI: 10.1109/ARSO.2017.8025197
  
  
• AAAI Presidential Panel on Long-Term AI Futures, Association for the Advancement of AI (AAAI), 2008-2009.
  
  
• W.J. Dally, S.L. Graham, G.D. Hager, E. Horvitz, S. Kiesler, M. McQuade, E. Schmidt, Report to the President and Congress on Federally Funded R&D in Information Technology. August 2015, NITRD Working Group, President's Council of Advisors on Science and Technology (PCAST).
  
  
• E. Horvitz and T. Mitchell, From Data to Knowledge to Action: A Global Enabler for the 21st Century, Data Analytic Series, Computing Community Consortium, Computing Research Association (CRA), June 2010.
  
  
• E. Horvitz. From Data to Predictions and Decisions: Enabling Evidence-Based Healthcare, Data Analytic Series, Computing Community Consortium, Computing Research Association (CRA), September 2010.
  
  
• S. Graham, D. Estrin, E. Horvitz, I. Kohane, E. Mynatt, I. Sim. Information Technology Research Challenges for Healthcare: From Discovery to Delivery, Computing Community Consortium Whitepaper Series, Computing Research Association (CRA), May 2010.
  
  
• N. Eagle and E. Horvitz. AAAI Symposium on AI for Development: Preface to the Proceedings, Association for the Advancement of Artificial Intelligence, Stanford University, Stanford CA, March 2010.