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topics: |
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2011
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S. Saria, A. Duchi, and D. Koller (2011). "Discovering deformable motifs in continuous time-series data." International Joint Conference on Artificial Intelligence (IJCAI).
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2010
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P. Kumar, B. Packer, and D. Koller (2010). "Self-Paced Learning for Latent Variable Models." Advances in Neural Information Processing Systems (NIPS 2010).
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D. Vickrey, C. Lin, and D. Koller (2010). "Non-Local Contrastive Objectives." Proceedings of International Conference on Machine Learning (ICML).
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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).
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2009
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D. Koller and N. Friedman (2009). Probabilistic Graphical Models: Principles and Techniques. edited by . MIT Press. | bib
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topics: |
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D. Koller, Y. Bengio, D. Schuurmans, and L. Bottou (2009). Proceedings Advances in Neural Information Processing Systems (NIPS-08). . | bib
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2008
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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).
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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).
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topics: |
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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).
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topics: |
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J.C. Platt, D. Koller, Y. Singer, and S. Roweis (2008). Proceedings Advances in Neural Information Processing Systems (NIPS-07). . | bib
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2007
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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).
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topics: |
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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.
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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.
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topics: |
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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.
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topics: |
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2006
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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
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topics: |
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2005
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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).
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topics: |
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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
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topics: |
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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
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topics: |
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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).
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topics: |
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2004
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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).
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topics: |
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B. Taskar, V. Chatalbashev, and D. Koller (2004). "Learning Associative Markov Networks." Proceedings of the Twenty-First International Conference on Machine Learning (ICML).
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topics: |
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MN |
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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.
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topics: |
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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.
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topics: |
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2003
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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
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topics: |
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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
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topics: |
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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
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topics: |
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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).
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topics: |
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2002
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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
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topics: |
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E. Segal, D. Koller, and D. Ormoneit (2002). "Probabilistic Abstraction Hierarchies." Advances in Neural Information Processing Systems (NIPS 2001) (pp. 913-920).
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topics: |
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B. Taskar, P. Abbeel, and D. Koller (2002). "Discriminative Probabilistic Models for Relational Data." Proc. Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI).
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topics: |
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2001
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S. Tong and D. Koller (2001). "Active Learning for Structure in Bayesian Networks." Seventeenth International Joint Conference on Artificial Intelligence (IJCAI) (pp. 863-869).
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topics: |
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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
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topics: |
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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).
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topics: |
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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).
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topics: |
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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
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topics: |
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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).
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topics: |
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2000
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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).
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topics: |
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U. Chajewska and D. Koller (2000). "Utilities as Random Variables: Density Estimation and Structure Discovery." Proc. UAI--00 (pp. 63-71).
| bib/abs
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topics: |
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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
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topics: |
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1999
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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).
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topics: |
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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).
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topics: |
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X. Boyen and D. Koller (1999). "Approximate learning of dynamic models." Advances in Neural Information Processing Systems (NIPS) (pp. 396-402).
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topics: |
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1997
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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.
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topics: |
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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).
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topics: |
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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).
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topics: |
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1995
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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).
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topics: |
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