Toward Adaptive, Personalized Computing: Directions and Frontiers

 

Eric Horvitz

Microsoft Research

 

I will describe research on learning and reasoning about computer users' intentions, preferences, and attention, and highlight opportunities and challenges for machine learning at the human-computer interface. I will illustrate key ideas in the context of representative projects at Microsoft Research focusing on automation, user assistance, communications, and mixed-initiative interaction.  After reviewing concepts from the Coordinate, Lookout, Notification Platform, Seer, and Swish projects, I will discuss the prospect for new kinds of adaptation based on design-time and real-time learning. I will conclude with a discussion of challenge problems for learning in human-computer interaction.

References

·  E. Horvitz and J. Apacible. Learning and Reasoning about Interruption. Proceedings of the Fifth International Conference on Multimodal Interfaces, November 2003, Vancouver, BC, Canada.

 

·  E. Horvitz, A. Jacobs, D. Hovel. Attention-Sensitive Alerting, Proceedings of UAI '99, Conference on Uncertainty and Artificial Intelligence, July 1999, pp. 305-313.

 

·  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. Principles of Mixed-Initiative User Interfaces. Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, May 1999.

 

·  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 and E. Horvitz. Selective Perception Policies for Guiding Sensing and Computation in Multimodal Systems: A Comparative Analysis, Proceedings of the Fifth International Conference on Multimodal Interfaces, November 2003, ACM Press, Vancouver, BC, Canada.

·  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, July 1998.

·  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), 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.

·  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, IEEE Computer Society.

·  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. 

·  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.

·  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, pp. 201-210.

·  T. Paek and E. Horvitz. Conversation as Action Under Uncertainty, Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence (UAI-2000), Stanford, CA, June 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.

·  T. Paek, E. Horvitz, E. Ringger, Continuous Listening for Unconstrained Spoken Dialog, 6th International Conference on Spoken Language Processing (ICSLP 2000), Beijing, November 2000.

·  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, 119-128.

·  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.

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·  D. Heckerman and E. Horvitz. Inferring Informational Goals from Free-Text Queries. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, July 1998.

·  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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