Eric Horvitz: Online papers and abstracts

• 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. 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, To appear, International Journal on Computer Vision and Image Understanding (CVIU).
  
  
• 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.
  
  
• 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, To appear.
  
  
• 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.
  
  
• 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, Zürich, Switzerland.
  
  
• 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, 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.
  
  
• 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.
  
  
• 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.
  
  
• 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.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.
  
  
• 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.
  
  
• 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. 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, M., E. Horvitz, and S. Wilhite (2004). A Diary Study of Task Switching and Interruptions, Proceedings of CHI 2004, Human Factors in Computing Systems. Vienna, April 2004.
  
  
• 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, 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 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.
  
  
• 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.
  
  
• 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. Uncertainty, Action, and Interaction: In Pursuit of Mixed-Initiative Computing. Intelligent Systems, Sept./ October Issue, 2000, IEEE Computer Society.
  
  
• 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.
  
  
• David M. Pennock, Eric Horvitz, Steve Lawrence, and C. Lee Giles. Collaborative filtering by personality diagnosis: A hybrid memory- and model-based approach (postscript), In: Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence (UAI-2000), Stanford, CA, June 2000.



• 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.
  
  
• T. Paek, E. Horvitz, E. Ringger. Continuous Listening for Unconstrained Spoken Dialog, 6th International Conference on Spoken Language Processing (ICSLP 2000), Beijing, November 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 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.
  
  
• 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.
  
  
• 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.
  
  
• K. Hinckley, J. Pierce, M. Sinclair, E. Horvitz, Sensing Techniques for Mobile Interaction (color version of paper), ACM UIST 2000 Symposium on User Interface Software and Technology, November 2000, San Diego, California, pp. 91-100. (Best paper Award.) Video demo (mpeg) available – approx. 3 minutes.
  
  
• 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.
  
  
• 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.
  
  
• 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.
  
  
• 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.
  
  
• 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.
  
  
• 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. 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. 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, 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.
  
  
• 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.
  
  
• 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.
  
  
• E. Horvitz and A. Klein. Reasoning, Metareasoning, and Mathematical Truth: 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.
  
  
• 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.
  
  
• 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, 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 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.
  
  
• 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.
  
  
• 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.
  
  
• 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.
  
  
• E. Horvitz and G. Rutledge. Time-Dependent Utility and Action Under Uncertainty. Uncertainty in Artificial Intelligence, Los Angeles, pp. 151-158. Morgan Kaufman, 1991.
  
  
• 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.
  
  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.
  
  
• 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.
  
  
• 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.
  
  
• B.N. Nathwani, D.E. Heckerman, E.J. Horvitz, and T.L. Lincoln. Integrated expert systems and videodisc in surgical pathology: An overview. Human Pathology 1990;21:11-27
  
  
• E. Horvitz. Computation and Action under Bounded Resources. PhD Dissertation, Stanford University, 1990.
  
  
• 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.
  
  
• 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.
  
  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. Also, Stanford University Computer Science Department Technical Report KSL-90-09, 1990.
  
  
• 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.
  
  
• 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. Also, Stanford University Computer Science Department Technical Report KSL-90-68, 1990. Download report.
  
  
• 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, 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.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.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.
  
  
• E.J. Horvitz, Problem-Solving Design: Reasoning about Computational Value, Tradeoffs, and Resources. Proceedings of the 1987 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, July 1986.
  
  
• 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.
  
  
• 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, Proceedings of the Third Conference on Uncertainty in Artificial Intelligence, Seattle, Washington. July 1987. Association for Uncertainty and Artificial Intelligence. pp. 429-444. Also 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
  
  
• 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, and C.P. Langlotz. A Framework for Comparing Alternative Formalisms for Plausible Reasoning. Proceedings of AAAI-86, National Conference on Artificial Intelligence, Philadelphia, PA, Morgan Kaufmann, July 1986, pp. 210-214.
  
  
• E.J. Horvitz and D.E. Heckerman, The Inconsistent Use of Measures of Certainty in Artificial Intelligence Research, Proceedings of UAI-86, Conference on Uncertainty in Artificial Intelligence, Philadelphia, July 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.
  
  

Online abstracts of papers from the Stanford University list.