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Daphne Koller Publications
Research Areas (all)Publication TypeYears
BNBayesian Networks   BMBiology and Medicine
DMDecision Making   HMHybrid Models
LTWLanguage and Web   LGMLearning Graphical Models
MNMarkov Networks   RPMRicher Probabilistic Models
RPRobotics and Perception   SLSupervised Learning
TPMTemporal Probabilistic Models  
JJournal Article
CConference Paper
BBook
ChBook Chapter
TTechnical Report
PhDPhD Disseration
1985 - 1989
1990 - 1994
1995 - 1999
2000 - 2004
2005 - 2009
2010 - 2014

TypeReferenceDownload
topics: BNBMDMHMLTWLGMMNRPMRPSLTPM

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 pdf
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 pdf
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 pdf
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 pdf
topics:                LGM MN            

2009
B   D. Koller and N. Friedman (2009). Probabilistic Graphical Models: Principles and Techniques. edited by . MIT Press.bib html
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 html
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 pdf
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 pdf
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 pdf ppt
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 html
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 pdf
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 pdf
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 pdf
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 pdf
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 pdf
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 pdf
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 pdf ps.gz
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 pdf
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf
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 pdf ps.gz
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 pdf ps.gz
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 pdf
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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 pdf ps.gz
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               

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