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.

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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