BOOK CHAPTERS

• "Game Theory," by D. Koller. Invited contribution to the MIT Encyclopedia for Cognitive Science, Robert A. Wilson and Frank C. Keil, Eds., MIT Press, 1999, pages 338--340.
• Learning Probabilistic Relational Models, L. Getoor, N. Friedman, D. Koller, and A. Pfeffer. Invited contribution to the book Relational Data Mining, S. Dzeroski and N. Lavrac, Eds., Springer-Verlag, 2001 (to appear).
• Sampling in Factored Dynamic Systems, by D. Koller and U. Lerner. Invited contribution to the book Sequential Monte Carlo Methods in Practice, A. Doucet, J.F.G. de Freitas, and N. Gordon, Eds., Springer-Verlag 2000 (to appear).

INVITED PAPERS

• Structured Representations and Intractibility, Position Paper for the AI Working Group, of the ACM Workshop on Strategic Directions in Computing Research, 1996. Appeared electronically in ACM Computing Surveys, Vol. 28, No. 4.
• Information agents: A new challenge for AI, D. Koller and Y. Shoham. IEEE Expert, June 1996, pages 8-10.
• A Response to `Believing on the basis of evidence', F. Bacchus, A.J. Grove, J.Y. Halpern, and D. Koller. Computational Intelligence, 10:1, 1994.
• Generating degrees of belief from statistical information: An overview, F. Bacchus, A.J. Grove, J.Y. Halpern, and D. Koller. Proceedings of the 13th Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS), Bombay, India, 1993, pages 318-325.

PUBLICATIONS in REFEREED JOURNALS

• Representations and Solutions for Game-Theoretic Problems, D. Koller and A.J. Pfeffer. Artificial Intelligence, 94(1), July 1997, pages 167--215.
• From statistical knowledge bases to degrees of belief, F. Bacchus, A.J. Grove, J.Y. Halpern, and D. Koller. Artificial Intelligence, 87, February 1997, pages 75--143.
• Adaptive probabilistic networks with hidden variables, J. Binder, D. Koller, S.J. Russell, and K. Kanazawa. Machine Learning Journal, 29(2-3), November 1997, pages 213-244.
• (De)randomized construction of small sample spaces in NC, D.R. Karger and D. Koller. Journal of Computer and System Sciences, 55(3), December 1997, pages 402-413. (Special issue of selected papers from FOCS '94, by invitation)
• Finding mixed strategies with small supports in extensive form games, D. Koller and N. Megiddo. International Journal of Game Theory, 25:1, March 1996, pages 73-92.
• Minmax equilibria in team games, B. von Stengel and D. Koller. Games and Economic Behavior, 21, December 1997, pages 309-321.
• Efficient computation of equilibria for extensive two-person games, D. Koller, N. Megiddo, and B. von Stengel. Games and Economic Behavior, 14:2, June 1996, pages 247-259.
• Asymptotic conditional probabilities: The unary case, A.J. Grove, J.Y. Halpern, and D. Koller. SIAM Journal on Computing, 25:1, February 1996, pages 1--51.
• Asymptotic conditional probabilities: The non-unary case, A.J. Grove, J.Y. Halpern, and D. Koller. Journal of Symbolic Logic, 61:1, March 1996, pages 250--276.
• Random worlds and maximum entropy, A.J. Grove, J.Y. Halpern, and D. Koller. Journal of Artificial Intelligence Research, August 1994, pages 33--88.
• Constructing small sample spaces satisfying given constraints, D. Koller and N. Megiddo. SIAM Journal on Discrete Mathematics, 7:2, May 1994, pages 260--274.
• Finding the hidden path: time bounds for all-pairs shortest paths, D.R. Karger, D. Koller, and S.J. Phillips. SIAM Journal on Computing 22:6, December 1993, pages 1199-1217.
• The complexity of two-person zero-sum games in extensive form, D. Koller and N. Megiddo. Games and Economic Behavior 4:4, October 1992, pages 528--552.
• Fault-tolerant critical section management in asynchronous environments, A. Bar-Noy, D. Dolev, D. Koller, and D. Peleg. Information and Computation 95:1, November 1991, pages 1--20.

PUBLICATIONS in REFEREED CONFERENCES

• Policy Iteration for Factored MDPs, D. Koller and R. Parr. Proceedings of the 16th Annual Conference on Uncertainty in AI (UAI), Stanford, California, July 2000, pages 326--334.
• Utilities as Random Variables: Density Estimation and Structure Discovery U. Chajewska and D. Koller. Proceedings of the 16th Annual Conference on Uncertainty in AI (UAI), Stanford, California, July 2000, pages 63--71.
• Being Bayesian about Network Structure N. Friedman and D. Koller. Proceedings of the 16th Annual Conference on Uncertainty in AI (UAI), Stanford, California, July 2000, pages 201--210.
• Probabilistic Models for Agents' Beliefs and Decisions B. Milch and D. Koller. Proceedings of the 16th Annual Conference on Uncertainty in AI (UAI), Stanford, California, July 2000, pages 389--396.
• Support Vector Machine Active Learning with Applications to Text Classification, S. Tong and D. Koller. Proceedings of the 17th International Conference on Machine Learning (ICML), 2000, Stanford, California, June 2000, pages 999--1006.
• Making Rational Decisions using Adaptive Utility Elicitation, U. Chajewska, D. Koller, and R. Parr. Proceedings of the 17th National Conference on Artificial Intelligence (AAAI), 2000, Austin, Texas, August 2000, pages 363--369.
• Semantics and Inference for Recursive Probability Models, A. Pfeffer and D. Koller. Proceedings of the 17th National Conference on Artificial Intelligence (AAAI), 2000, Austin, Texas, August 2000, pages 538--544.
• Restricted Bayes Optimal Classifiers, S. Tong and D. Koller. Proceedings of the 17th National Conference on Artificial Intelligence (AAAI), Austin, Texas, August 2000, pages 658--664.
• Bayesian Fault Detection and Diagnosis in Dynamic Systems, U. Lerner, R. Parr, D. Koller, and G. Biswas. Proceedings of the 17th National Conference on Artificial Intelligence (AAAI), August 2000, pages 531--537.
• Using learning for approximation in stochastic processes, D. Koller and R. Fratkina. Proceedings of the 15th International Conference on Machine Learning (ML), Madison, Wisconsin, July 1998, pages 287--295.
• Reinforcement learning using approximate belief states, A.C. Rodriguez, R. Parr, and D. Koller. Advances in Neural Information Processing Systems (NIPS), Denver, Colorado, December 1999.
• Policy search via density estimation, by A. Ng, R. Parr, and D. Koller. Advances in Neural Information Processing Systems (NIPS), Denver, Colorado, December 1999.
• SPOOK: A system for probabilistic object-oriented knowledge representation A. Pfeffer, D. Koller, B. Milch, and K. Takusagawa, In Proceedings of the 15th Annual Conference on Uncertainty in AI (UAI), Stockholm, Sweden, August 1999, pages 541--550.
• A General Algorithm for Approximate Inference and its Application to Hybrid Bayes Nets D. Koller, U. Lerner, and D. Angelov, In Proceedings of the 15th Annual Conference on Uncertainty in AI (UAI), Stockholm, Sweden, August 1999, pages 324--333.
• Discovering the Hidden Structure of Complex Dynamic Systems X. Boyen, N. Friedman, and D. Koller. Proceedings of the 15th Annual Conference on Uncertainty in AI (UAI), Stockholm, Sweden, August 1999, pages 206--215.
• Exploiting the Architecture of Dynamic Systems, X. Boyen and D. Koller. Proceedings of the 16th National Conference on Artificial Intelligence (AAAI), 1999, pages 313--320.
• Learning Probabilistic Relational Models, N. Friedman, L. Getoor, D. Koller and A. Pfeffer. Proceedings of the 16th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, August 1999, pages 1300--1307.
• Computing factored value functions for policies in structured MDPs, D. Koller and R. Parr. Proceedings of the 16th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, August 1999, pages 1332--1339.
• Efficient Reinforcement Learning in Factored MDPs, M. Kearns and D. Koller. Proceedings of the 16th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, August 1999, pages 740--747.
• Approximate learning of dynamic models, X. Boyen and D. Koller. Proceedings of the 12th Annual Conference on Neural Information Processing Systems, Denver, Colorado, December 1998, pages 396--402.
• Structured representation of complex stochastic systems, N. Friedman, D. Koller, and A. Pfeffer. Proceedings of the 15th National Conference on Artificial Intelligence (AAAI), Madison, Wisconsin, July 1998, pages 157--164.
• Probabilistic frame-based systems, D. Koller and A. Pfeffer. Proceedings of the 15th National Conference on Artificial Intelligence (AAAI), Madison, Wisconsin, July 1998, pages 580--587.
• Tractable inference for complex stochastic processes, X. Boyen and D. Koller, Proceedings of the 14th Annual Conference on Uncertainty in AI (UAI), Madison, Wisconsin, July 1998, pages 33--42.
• Using learning for approximation in stochastic processes, D. Koller and R. Fratkina. Proceedings of the 15th International Conference on Machine Learning (ICML), Madison, Wisconsin, July 1998, pages 287--295.
• Update rules for parameter estimation in Bayesian networks, E. Bauer, D. Koller, and Y. Singer. Proceedings of the 13th Annual Conference on Uncertainty in AI (UAI), Providence, Rhode Island, August 1997, pages 3--13.
• Object-Oriented Bayesian Networks, D. Koller and A. Pfeffer. Proceedings of the 13th Annual Conference on Uncertainty in AI (UAI), Providence, Rhode Island, August 1997, pages 302--313. Winner of the UAI '97 best student paper award.
• Nonuniform dynamic discretization in hybrid networks, A.V. Kozlov and D. Koller. Proceedings of the 13th Annual Conference on Uncertainty in AI (UAI), Providence, Rhode Island, August 1997, pages 314--325.
• Effective Bayesian Inference for Stochastic Programs, D. Koller, D. McAllester, and A. Pfeffer. Proceedings of the 14th National Conference on Artificial Intelligence (AAAI), Providence, Rhode Island, August 1997, pages 740--747.
• P-Classic: A tractable probabilistic description logic, D. Koller, A. Levy, and A. Pfeffer. Proceedings of the 14th National Conference on Artificial Intelligence (AAAI), Providence, Rhode Island, August 1997, pages 390--397.
• Learning probabilities for noisy first-order rules, D. Koller and A. Pfeffer. Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI), Nagoya, Japan, August 1997, pages 1316--1321.
• Hierarchically classifying documents using very few words, D. Koller and M. Sahami. Proceedings of the 14th International Conference on Machine Learning (ICML), Nashville, Tennessee, July 1997, pages 170--178.
• Using probabilistic information in data integration, D. Florescu, D. Koller, and A. Levy. Conference on Very Large Databases (VLDB), Athens, Greece, August 1997.
• Context-Specific Independence in Bayesian Networks, C. Boutilier, N. Friedman, M. Goldszmidt, and D. Koller. Proceedings of the 12th Annual Conference on Uncertainty in AI (UAI), Portland, Oregon, August 1996, pages 115--123.
• Toward optimal feature selection, D. Koller and M. Sahami. Proceedings of the 13th International Conference on Machine Learning (ICML), Bari, Italy, July 1996, pages 284--292.
• Irrelevance and conditioning in first-order probabilistic logic, D. Koller and J.Y. Halpern. Proceedings of the 13th National Conference on Artificial Intelligence (AAAI), Portland, Oregon, August 1996, pages 569--576.
• First-order conditional logic revisited, N. Friedman, J.Y. Halpern, and D. Koller. Proceedings of the 13th National Conference on Artificial Intelligence (AAAI), Portland, Oregon, August 1996, pages 1305--1312.
• Stochastic simulation algorithms for dynamic probabilistic networks, K. Kanazawa, D. Koller, and S.J. Russell. Proceedings of the 11th Annual Conference on Uncertainty in AI (UAI), Montreal, Canada, August 1995, pages 346--351.
• Local Learning in Probabilistic Networks with Hidden Variables, S.J. Russell, J. Binder, D. Koller, and K. Kanazawa. Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI), Montreal, Canada, August 1995, pages 1146--1152.
• Representation dependence in probabilistic inference, J.Y. Halpern and D. Koller. Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI), Montreal, Canada, August 1995, pages 1853--1860.
• Generating and solving imperfect information games, D. Koller and A.J. Pfeffer. Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI), Montreal, Canada, August 1995, pages 1185--1192.
• Constructing flexible dynamic belief networks from first-order probabilistic knowledge bases, S. Glesner and D. Koller. {\em Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU), Fribourg, Switzerland, July 1995. In Lecture Notes in Artificial Intelligence, Ch. Froidevaux and J. Kohlas (Eds.), Springer Verlag, 1995, pages 217-226.
• A game-theoretic classification of interactive complexity classes, J. Feigenbaum, D. Koller, and P. Shor. Proceedings of the 10th Annual IEEE Conference on Structure in Complexity Theory (STRUCTURES), Minneapolis, Minnesota, June 1995, pages 227-237.
• (De)randomized construction of small sample spaces in NC, D.R. Karger and D. Koller. Proceedings of the 35nd Annual Symposium on the Foundations of Computer Science (FOCS), Santa Fe, New Mexico, November 1994, pages 252-263.
• Generating new beliefs from old, F. Bacchus, A.J. Grove, and J.Y. Halpern, and D. Koller. Proceedings of the 10th Annual Conference on Uncertainty in AI (UAI), Seattle, Washington, July 1994, pages 37--45.
• Forming beliefs about a changing world, F. Bacchus, A.J. Grove, and J.Y. Halpern, and D. Koller. Proceedings of the 12th National Conference on Artificial Intelligence (AAAI), Seattle, Washington, August 1994, pages 222--229.
• Fast algorithms for finding randomized strategies in game trees, D. Koller, N. Megiddo, and B. von Stengel. Proceedings of the 26th ACM Symposium on Theory of Computing (STOC), Montreal, Canada, May 1994, pages 750--759.
• Statistical foundations for default reasoning, F. Bacchus, A.J. Grove, J.Y. Halpern, and D. Koller. Proceedings of the 13th International Joint Conference on Artificial Intelligence (IJCAI), Chambery, France, August 1993, pages 563--569.
• Constructing small sample spaces satisfying given constraints, D. Koller and N. Megiddo. Proceedings of the 25th ACM Symposium on Theory of Computing (STOC), San Diego, California, May 1993, pages 268--277.
• A logic for approximate reasoning, D. Koller and J.Y. Halpern. Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning (KR), Cambridge, Massachusetts, October 1992, pages 153-164.
• From statistics to beliefs, F. Bacchus, A.J. Grove, J.Y. Halpern, and D. Koller. Proceedings of the 10th National Conference on Artificial Intelligence (AAAI), San Jose, California, July 1992, pages 602-608.
• Random worlds and maximum entropy, A.J. Grove, J.Y. Halpern, and D. Koller. Proceedings of the 7th Annual IEEE Symposium on Logic in Computer Science (LICS), Santa Cruz, California, June 1992, pages 22-33.
• Asymptotic conditional probabilities for first-order logic, A.J. Grove, J.Y. Halpern, and D. Koller. Proceedings of the 24th ACM Symposium on Theory of Computing (STOC), Victoria, Canada, May 1992, pages 294-305.
• Finding the hidden path: time bounds for all-pairs shortest paths, D.R. Karger, D. Koller, and S.J. Phillips. Proceedings of the 32nd Annual Symposium on the Foundations of Computer Science (FOCS), San Juan, Puerto Rico, October 1991, pages 560-568.
• Probability estimation in face of irrelevant information, A.J. Grove and D. Koller. Proceedings of the 7th Annual Conference on Uncertainty in AI (UAI), Los Angeles, California, July 1991, pages 127-134.
• Fault-tolerant critical section management in asynchronous environments, A. Bar-Noy, D. Dolev, D. Koller, and D. Peleg. Proceedings of the Third International Workshop on Distributed Algorithms (WDAG), Nice, France, September 1989, pages 13-23.
• Achievable cases in an asynchronous environment, H. Attiya, A. Bar-Noy, D. Dolev, D. Koller, D. Peleg, and R. Reischuk, Proceedings of the 28th Annual Symposium on the Foundations of Computer Science (FOCS), Los Angeles, California, October 1987, pages 337-346.