Research overview
I'm interested in principles of sensing, inference, and decision making under uncertainty. My interests include human decision making and computational models of reflection and action.
Beyond theoretical models, I pursue applications in several realms, including time-critical decision making, scientific exploration, information retrieval, and healthcare--with goals of understanding how computational models perform amidst real-world complexities, and of deploying valuable systems.
Related interests include information triage and alerting that takes human attention into consideration, spanning work on notification systems, surprise modeling, multitasking, and psychological studies of interruption and recovery. Other interests include principles of mixed-initiative interaction that can support fluid, efficient collaborations between people and computing systems, methods for guiding computer actions in accordance with the preferences of people, search and information retrieval, and collaboration. I've also been long interested in offline and real-time optimization of the expected value of
computational systems under limited and varying resources. Areas of concentration in this realm include
flexible or anytime computation, ideal metareasoning
for guiding computation, compilation
for reducing real-time deliberation, ongoing, continual computation, and the construction of bounded-optimal reasoning systems--systems that
maximize the expected utility of the people they serve, given the
expected costs of reasoning, the problems
encountered over time, and assertions about a system's constitution. Research in this arena includes
tackling hard reasoning problems with learning and decision making methods.
My organization within Microsoft Research includes groups focused on machine learning and decision making, search and retrieval, human-computer interaction, ecommerce, hardware devices, computational theory, and cryptography.
I'm serving as President of the Association for the Advancement of Artificial Intelligence (AAAI). See AAAI's web site for more information on events in the AI community. News stories and introductory information on topics in AI are available at AAAI's AI Topics site.
Selected publications by topic
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Search, Services, and Web
- J. Leskovec and E. Horvitz. Planetary-Scale Views on a Large Instant-Messaging Network, Proceedings of WWW 2008, Beijing, China, April 2008.
- A. Krause and E. Horvitz. A Utility-Theoretic Approach to Privacy and Personalization, Proceedings of AAAI-08, Chicago, Illinois, July 2008.
- E. Kamar, E. Horvitz, C. Meek. Mobile Opportunistic Commerce: Mechanisms, Architecture, and Application, Proceedings of AAMAS 2008, Estoril, Portugal, May 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.
- 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.
- 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.
- C. R. Anderson and E. Horvitz. Web Montage: A Dynamic Personalized Start Page, Eleventh International World Wide Web Conference, Honolulu, Hawaii, May 2002.
- D. Azari, E. Horvitz, S. Dumais, E. Brill. Actions, Answers, and Uncertainty: A Decision Making Perspective on Web-Based Question Answering, Information Processing and Management, 40(5), 2004, pp. 849-868.
- 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.
- P. N. Bennett, S. T. Dumais, and E. Horvitz. The Combination of Text Classifiers using Reliability Indicators. Information Retrieval, 2003.
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Learning, sensing, and reasoning under uncertainty
- A. Kause, 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. 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.
- 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.
- N. Oliver and E. Horvitz. Selective Perception Policies for Guiding Sensing and Computation in Multimodal Systems: A Comparative Analysis, Fifth International Conference on Multimodal Interfaces, November 2003.
- 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).
- J. Krumm and E Horvitz. Predestination: Inferring Destinations from Partial Trajectories, Ubicomp 2006: Eighth International Conference on Ubiquitous Computing, September 2006.
- E. Horvitz, P. Koch, C.M. Kadie, and A. Jacobs. Coordinate: Probabilistic Forecasting of Presence and Availability.Eighteenth Conference on Uncertainty and Artificial Intelligence, July 2002, pp. 224-233.
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- E. Horvitz, Y. Ruan, C. Gomes, H. Kautz, B. Selman, D. M. Chickering. A Bayesian Approach to Tackling Hard Computational Problems. Seventeenth Conference on Uncertainty in Artificial Intelligence, August 2001.
- E. Horvitz. Principles and Applications of Continual Computation. Artificial Intelligence Journal, February 2001.
- H. Kautz, E. Horvitz, Y. Ruan, C. Gomes, B. Selman. Dynamic Restart Policies. Eighteenth National Conference on Artificial Intelligence, July 2002.
- 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, July 2004.
- E. Horvitz and A. Klein.
Studies of Theorem Proving under Limited Resources. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence,
August 1995.
- 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.
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Attention, Memory, and Human-Computer Interaction
- 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, 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.
- E. Horvitz and J. Apacible. Learning and Reasoning about Interruption. Fifth International Conference on Multimodal Interfaces, November 2003.
- 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.
- 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, 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. Principles of Mixed-Initiative User Interfaces.
Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, May 1999.
- 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.
- 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.
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Attention-Sensitive Design
- 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, 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.
- M. van Dantzich, D. Robbins, E. Horvitz, M. Czerwinski, Scope: Providing Awareness of Multiple Notifications at a Glance, Proceedings of AVI 2002, ACM Conference on Advanced Visual Interfaces, Trento, Italy, May 22-24, 2002. ACM Press.
- 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.
- 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.
J.ACM: Decisions, Uncertainty, and Computation Area
The Decisions, Uncertainty, and Computation
Area of the Journal of the
Association for Computing Machinery (JACM) serves
as a platform for publishing important
results on the computational foundations of methods and
processes for decision making under uncertainty.
Prospective authors
should refer to the submission information on the home page of the Journal of the Association for
Computing Machinery (JACM). Questions about appropriateness of submissions
should be directed to the Area Editor at horvitz@microsoft.com.
Edited collections
Several fun links...
Feel free to send email if you have any questions or comments about material, pointers on these web pages.
