Papers Daphne Koller Publications Research Areas (all) Publication Type Years BN Bayesian Networks    BM Biology and Medicine DM Decision Making    HM Hybrid Models LTW Language and Web    LGM Learning Graphical Models MN Markov Networks    RPM Richer Probabilistic Models RP Robotics and Perception    SL Supervised Learning TPM Temporal Probabilistic Models    J Journal Article C Conference Paper B Book Ch Book Chapter T Technical Report PhD PhD Disseration 1985 - 1989 1990 - 1994 1995 - 1999 2000 - 2004 2005 - 2009 2010 - 2014 Type Reference Download topics: BN BM DM HM LTW LGM MN RPM RP SL TPM 2011 C   S. Saria, A. Duchi, and D. Koller (2011). "Discovering deformable motifs in continuous time-series data." International Joint Conference on Artificial Intelligence (IJCAI). bib topics:                LGM             TPM 2010 C   P. Kumar, B. Packer, and D. Koller (2010). "Self-Paced Learning for Latent Variable Models." Advances in Neural Information Processing Systems (NIPS 2010). bib topics:                LGM       RP       C   D. Vickrey, C. Lin, and D. Koller (2010). "Non-Local Contrastive Objectives." Proceedings of International Conference on Machine Learning (ICML). bib topics:                LGM MN             C   V. Jojic, S. Gould, and D. Koller (2010). "Fast and smooth: Accelerated dual decomposition for MAP inference." Proceedings of International Conference on Machine Learning (ICML). bib topics:                LGM MN             2009 B   D. Koller and N. Friedman (2009). Probabilistic Graphical Models: Principles and Techniques. edited by . MIT Press. bib topics: BN             LGM MN             B   D. Koller, Y. Bengio, D. Schuurmans, and L. Bottou (2009). Proceedings Advances in Neural Information Processing Systems (NIPS-08). . bib topics:                LGM       RP SL    2008 C   V. Ganapathi, D. Vickrey, J. Duchi, and D. Koller (2008). "Constrained Approximate Maximum Entropy Learning." Proceedings of the Twenty-fourth Conference on Uncertainty in AI (UAI). bib topics:                LGM MN             C   J. Duchi, S. Gould, and D. Koller (2008). "Projected Subgradient Methods for Learning Sparse Gaussians." Proceedings of the Twenty-fourth Conference on Uncertainty in AI (UAI). bib topics:          HM    LGM MN             C   G. Elidan, B. Packer, G. Heitz, and D. Koller (2008). "Convex Point Estimation using Undirected Bayesian Transfer Hierarchies." Proceedings of the Twenty-fourth Conference on Uncertainty in AI (UAI). bib topics:                LGM MN       SL    B   J.C. Platt, D. Koller, Y. Singer, and S. Roweis (2008). Proceedings Advances in Neural Information Processing Systems (NIPS-07). . bib topics:                LGM       RP SL    2007 C   S.-I. Lee, V. Ganapathi, and D. Koller (2007). "Efficient Structure Learning of Markov Networks using L1-Regularization." Advances in Neural Information Processing Systems (NIPS 2006). bib topics:                LGM MN             Ch   L. Getoor, N. Friedman, D. Koller, A. Pfeffer, and B. Taskar (2007). "Probabilistic Relational Models." In L. Getoor and B. Taskar, editors, Introduction to Statistical Relational Learning. bib topics:                LGM    RPM          Ch   D. Heckerman, C. Meek, and D. Koller (2007). "Probabilistic Entity-Relationship Models, PRMs, and Plate Models." In L. Getoor and B. Taskar, editors, Introduction to Statistical Relational Learning. bib topics:                LGM    RPM          Ch   B. Taskar, P. Abbeel, M.-F. Wong, and D. Koller (2007). "Relational Markov Networks." In L. Getoor and B. Taskar, editors, Introduction to Statistical Relational Learning. bib topics:                LGM MN RPM          2006 J   P. Abbeel, D. Koller, and A.Y. Ng (2006). "Learning Factor Graphs in Polynomial Time & Sample Complexity." Journal of Machine Learning Research, 7, 1743-1788. [older version, 2005] bib topics:                LGM MN             2005 C   M. Teyssier and D. Koller (2005). "Ordering-based Search: A Simple and Effective Algorithm for Learning Bayesian Networks." Proceedings of the Twenty-first Conference on Uncertainty in AI (UAI) (pp. 584-590). bib/abs topics: BN             LGM                C   P. Abbeel, D. Koller, and A.Y. Ng (2005). "Learning Factor Graphs in Polynomial Time & Sample Complexity." Proceedings of the Twenty-first Conference on Uncertainty in AI (UAI) (pp. 1-9). [newer version, 2006] bib/abs topics:                LGM MN             J   E. Segal, D. Pe'er, A. Regev, D. Koller, and N. Friedman (2005). "Learning Module Networks." Journal of Machine Learning Research, 6, 557-588. [older version, 2003] bib/abs topics:    BM          LGM    RPM          C   B. Taskar, V. Chatalbashev, D. Koller, and C. Guestrin (2005). "Learning Structured Prediction Models: A Large Margin Approach." Twenty-Second International Conference on Machine Learning (ICML). bib/abs topics:    BM          LGM    RPM    SL    2004 C   A.J. Battle, E. Segal, and D. Koller (2004). "Probabilistic Discovery of Overlapping Cell Processes and Their Regulation." Eight Annual International Conference on Research in Computational Molecular Biology (RECOMB). bib/abs topics:    BM          LGM                C   B. Taskar, V. Chatalbashev, and D. Koller (2004). "Learning Associative Markov Networks." Proceedings of the Twenty-First International Conference on Machine Learning (ICML). bib/abs topics:                LGM MN             C   B. Taskar, D. Klein, M. Collins, D. Koller, and C. Manning (2004). "Max-Margin Parsing." Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP). Winner of the Best Paper Award. bib/abs topics:             LTW LGM          SL    C   B. Taskar, C. Guestrin, and D. Koller (2004). "Max-Margin Markov Networks." Advances in Neural Information Processing Systems (NIPS 2003). Winner of the Best Student Paper Award. bib/abs topics:             LTW LGM MN       SL    2003 J   N. Friedman and D. Koller (2003). "Being Bayesian about Bayesian Network Structure:A Bayesian Approach to Structure Discovery in Bayesian Networks.." Machine Learning, 50(1--2), 95-125. Full version of UAI 2000 paper. [older version, 2000] bib/abs topics: BN             LGM                C   E. Segal, D. Pe'er, A. Regev, D. Koller, and N. Friedman (2003). "Learning Module Networks." Proc. Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI) (pp. 525-534). [newer version, 2005] bib/abs topics:    BM          LGM    RPM          C   U. Nodelman, C.R. Shelton, and D. Koller (2003). "Learning Continuous Time Bayesian Networks." Proc. Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI) (pp. 451-458). Winner of the Best Paper Award. bib/abs topics:                LGM             TPM C   B. Taskar, M.-F. Wong, and D. Koller (2003). "Learning on the Test Data: Leveraging `Unseen' Features." Proc. Twentieth International Conference on Machine Learning (ICML). bib/abs topics:             LTW LGM          SL    2002 J   L. Getoor, N. Friedman, D. Koller, and B. Taskar (2002). "Learning probabilistic models of Relational Structure." Journal of Machine Learning Research, 3, 679-707. [older version, 2001] bib topics:             LTW LGM    RPM          C   E. Segal, D. Koller, and D. Ormoneit (2002). "Probabilistic Abstraction Hierarchies." Advances in Neural Information Processing Systems (NIPS 2001) (pp. 913-920). bib/abs topics:                LGM                C   B. Taskar, P. Abbeel, and D. Koller (2002). "Discriminative Probabilistic Models for Relational Data." Proc. Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI). bib/abs topics:             LTW LGM    RPM    SL    2001 C   S. Tong and D. Koller (2001). "Active Learning for Structure in Bayesian Networks." Seventeenth International Joint Conference on Artificial Intelligence (IJCAI) (pp. 863-869). bib/abs topics:                LGM                C   L. Getoor, N. Friedman, D. Koller, and B. Taskar (2001). "Learning probabilistic models of Relational Structure." Proceedings of the Eighteenth International Conference on Machine Learning (pp. 170-177). [newer version, 2002] bib/abs topics:             LTW LGM    RPM          C   L. Getoor, B. Taskar, and D. Koller (2001). "Using Probabilistic Models for Selectivity Estimation." Proceedings of ACM SIGMOD International Conference on Management of Data (pp. 461-472). bib/abs topics:                LGM    RPM          C   B. Taskar, E. Segal, and D. Koller (2001). "Probabilistic Supervised Learning and Clustering in Relational Data." Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI) (pp. 870-876). bib/abs topics:             LTW LGM    RPM    SL    C   S. Tong and D. Koller (2001). "Active Learning for Parameter Estimation in Bayesian Networks." Conference on Advances in Neural Infomation Processing Systems (NIPS 2000). bib/abs topics:                LGM                Ch   L. Getoor, N. Friedman, D. Koller, and A. Pfeffer (2001). "Learning Probabilistic Relational Models." In S. D\vzeroski and N. Lavrac, editors, Relational Data Mining (pp. 307-335). bib topics:                LGM    RPM          2000 C   G. Elidan, N. Lotner, N. Friedman, and D. Koller (2000). "Discovering hidden variables: A structure-based approach." Advances in Neural Information Processing Systems (NIPS 2000). bib/abs topics: BN             LGM                C   U. Chajewska and D. Koller (2000). "Utilities as Random Variables: Density Estimation and Structure Discovery." Proc. UAI--00 (pp. 63-71). bib/abs topics:       DM       LGM                C   N. Friedman and D. Koller (2000). "Being Bayesian about Bayesian Network Structure:A Bayesian Approach to Structure Discovery in Bayesian Networks.." Proceedings of the 16th Annual Conference on Uncertainty in AI (UAI) (pp. 201-210). [newer version, 2003] bib/abs topics: BN             LGM                1999 C   X. Boyen, N. Friedman, and D. Koller (1999). "Discovering the hidden structure of complex dynamic systems." Proceedings of the 15th Annual Conference on Uncertainty in AI (UAI) (pp. 206-215). bib/abs topics:                LGM             TPM C   N. Friedman, L. Getoor, D. Koller, and A. Pfeffer (1999). "Learning probabilistic relational models." Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99) (pp. 1300-1309). bib/abs topics:                LGM    RPM          C   X. Boyen and D. Koller (1999). "Approximate learning of dynamic models." Advances in Neural Information Processing Systems (NIPS) (pp. 396-402). bib/abs topics:                LGM             TPM 1997 J   J. Binder, D. Koller, S.J. Russell, and K. Kanazawa (1997). "Adaptive probabilistic networks with hidden variables." Machine Learning, 29(2--3), 213-244. Full version of IJCAI '95 paper. bib/abs topics: BN             LGM                C   E. Bauer, D. Koller, and Y. Singer (1997). "Update rules for parameter estimation in Bayesian networks." Proc. Thirteenth Annual Conference on Uncertainty in AI (UAI) (pp. 3-13). bib/abs topics: BN             LGM                C   D. Koller and A. Pfeffer (1997). "Learning probabilities for noisy first-order rules." Proceedings of the International Joint Conference on Artificial Intelligence (pp. 1316-1321). bib/abs topics:                LGM    RPM          1995 C   S.J. Russell, J. Binder, D. Koller, and K. Kanazawa (1995). "Local learning in probabilistic networks with hidden variables." Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI) (pp. 1146-1152). bib topics: BN             LGM
	home | biography | research | papers | my group courses | professional activities | FAQ | personal