David Maxwell Chickering

David Maxwell Chickering, Christopher Meek: Finding Optimal Bayesian Networks. CoRR abs/1301.0561 (2013)

Eric Horvitz, Yongshao Ruan, Carla P. Gomes, Henry A. Kautz, Bart Selman, David Maxwell Chickering: A Bayesian Approach to Tackling Hard Computational Problems. CoRR abs/1301.2279 (2013)

Andrew Zimdars, David Maxwell Chickering, Christopher Meek: Using Temporal Data for Making Recommendations. CoRR abs/1301.2320 (2013)

David Maxwell Chickering, David Heckerman: A Decision Theoretic Approach to Targeted Advertising. CoRR abs/1301.3842 (2013)

David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie: Dependency Networks for Collaborative Filtering and Data Visualization. CoRR abs/1301.3862 (2013)

David Maxwell Chickering, David Heckerman: Fast Learning from Sparse Data. CoRR abs/1301.6685 (2013)

Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman: Learning Mixtures of DAG Models. CoRR abs/1301.7415 (2013)

David Maxwell Chickering, David Heckerman, Christopher Meek: A Bayesian Approach to Learning Bayesian Networks with Local Structure. CoRR abs/1302.1528 (2013)

David Maxwell Chickering: Learning Equivalence Classes of Bayesian Networks Structures. CoRR abs/1302.3566 (2013)

David Maxwell Chickering, David Heckerman: Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network. CoRR abs/1302.3567 (2013)

David Maxwell Chickering: A Transformational Characterization of Equivalent Bayesian Network Structures. CoRR abs/1302.4938 (2013)

David Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. CoRR abs/1302.6815 (2013)

Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek: ARMA Time-Series Modeling with Graphical Models. CoRR abs/1207.4162 (2012)

Max Chickering, Joseph Y. Halpern: Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (2004). CoRR abs/1208.5161 (2012)

Léon Bottou, Jonas Peters, Joaquin Quiñonero Candela, Denis Xavier Charles, Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard, Ed Snelson: Counterfactual Reasoning and Learning Systems. CoRR abs/1209.2355 (2012)

David Maxwell Chickering, Christopher Meek, David Heckerman: Large-Sample Learning of Bayesian Networks is NP-Hard. CoRR abs/1212.2468 (2012)

Christopher Meek, David Maxwell Chickering: Practically Perfect. CoRR abs/1212.2503 (2012)

Greg Linden, Christopher Meek, Max Chickering: The Pollution Effect: Optimizing Keyword Auctions by Favoring Relevant Advertising. CoRR abs/1109.6263 (2011)

Tim Paek, Michael Gamon, Scott Counts, David Maxwell Chickering, Aman Dhesi: Predicting the Importance of Newsfeed Posts and Social Network Friends. AAAI 2010

Sven Seuken, Denis Xavier Charles, Max Chickering, Sidd Puri: Market design & analysis for a P2P backup system. ACM Conference on Electronic Commerce 2010: 97-108

Denis Xavier Charles, Max Chickering, Nikhil R. Devanur, Kamal Jain, Manan Sanghi: Fast algorithms for finding matchings in lopsided bipartite graphs with applications to display ads. ACM Conference on Electronic Commerce 2010: 121-128

Sven Seuken, Denis Xavier Charles, Max Chickering, Sidd Puri: Market Design for a P2P Backup System. AMMA 2009: 55-57

Edith Law, Anton Mityagin, David Maxwell Chickering: Intentions: a game for classifying search query intent. CHI Extended Abstracts 2009: 3805-3810

Paul N. Bennett, David Maxwell Chickering, Anton Mityagin: Picture this: preferences for image search. KDD Workshop on Human Computation 2009: 25-26

Paul N. Bennett, David Maxwell Chickering, Anton Mityagin: Learning consensus opinion: mining data from a labeling game. WWW 2009: 121-130

Paul N. Bennett, Raman Chandrasekar, Max Chickering, Panagiotis G. Ipeirotis, Edith Law, Anton Mityagin, Foster J. Provost, Luis von Ahn (Eds.): Proceedings of the ACM SIGKDD Workshop on Human Computation, Paris, France, June 28, 2009. ACM 2009, isbn 978-1-60558-672-4

Yagil Engel, David Maxwell Chickering: Incorporating user utility into sponsored-search auctions. AAMAS (3) 2008: 1565-1568

Ben Carterette, Paul N. Bennett, David Maxwell Chickering, Susan T. Dumais: Here or There. ECIR 2008: 16-27

Guy Shani, David Maxwell Chickering, Christopher Meek: Mining recommendations from the web. RecSys 2008: 35-42

David Maxwell Chickering, Tim Paek: Personalizing influence diagrams: applying online learning strategies to dialogue management. User Model. User-Adapt. Interact. 17(1-2): 71-91 (2007)

Tim Paek, David Maxwell Chickering: Improving command and control speech recognition on mobile devices: using predictive user models for language modeling. User Model. User-Adapt. Interact. 17(1-2): 93-117 (2007)

Hila Becker, Christopher Meek, David Maxwell Chickering: Modeling Contextual Factors of Click Rates. AAAI 2007: 1310-1315

David Maxwell Chickering, Christopher Meek: On the incompatibility of faithfulness and monotone DAG faithfulness. Artif. Intell. 170(8-9): 653-666 (2006)

Tim Paek, David Maxwell Chickering: Evaluating the Markov assumption in Markov Decision Processes for spoken dialogue management. Language Resources and Evaluation 40(1): 47-66 (2006)

Kumar Chellapilla, David Maxwell Chickering: Improving Cloaking Detection using Search Query Popularity and Monetizability. AIRWeb 2006: 17-23

David Maxwell Chickering, David Heckerman, Christopher Meek: Large-Sample Learning of Bayesian Networks is NP-Hard. Journal of Machine Learning Research 5: 1287-1330 (2004)

Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek: ARMA Time-Series Modeling with Graphical Models. UAI 2004: 552-560

David Maxwell Chickering, Joseph Y. Halpern (Eds.): UAI '04, Proceedings of the 20th Conference in Uncertainty in Artificial Intelligence, Banff, Canada, July 7-11, 2004. AUAI Press 2004, isbn 0-9749039-0-6

David Maxwell Chickering, Christopher Meek, David Heckerman: Large-Sample Learning of Bayesian Networks is NP-Hard. UAI 2003: 124-133

Christopher Meek, David Maxwell Chickering: Practically Perfect. UAI 2003: 411-416

David Maxwell Chickering: Learning Equivalence Classes of Bayesian-Network Structures. Journal of Machine Learning Research 2: 445-498 (2002)

David Maxwell Chickering: Optimal Structure Identification With Greedy Search. Journal of Machine Learning Research 3: 507-554 (2002)

Christopher Meek, David Maxwell Chickering, David Heckerman: Autoregressive Tree Models for Time-Series Analysis. SDM 2002

David Maxwell Chickering, Christopher Meek: Finding Optimal Bayesian Networks. UAI 2002: 94-102

Eric Horvitz, Yongshao Ruan, Carla P. Gomes, Henry A. Kautz, Bart Selman, David Maxwell Chickering: A Bayesian Approach to Tackling Hard Computational Problems (Preliminary Report). Electronic Notes in Discrete Mathematics 9: 376-391 (2001)

David Maxwell Chickering, Christopher Meek, Robert Rounthwaite: Efficient Determination of Dynamic Split Points in a Decision Tree. ICDM 2001: 91-98

Eric Horvitz, Yongshao Ruan, Carla P. Gomes, Henry A. Kautz, Bart Selman, David Maxwell Chickering: A Bayesian Approach to Tackling Hard Computational Problems. UAI 2001: 235-244

Andrew Zimdars, David Maxwell Chickering, Christopher Meek: Using Temporal Data for Making Recommendations. UAI 2001: 580-588

David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie: Dependency Networks for Inference, Collaborative Filtering, and Data Visualization. Journal of Machine Learning Research 1: 49-75 (2000)

David Maxwell Chickering, David Heckerman: Targeted advertising with inventory management. ACM Conference on Electronic Commerce 2000: 145-149

David Maxwell Chickering, David Heckerman: A Decision Theoretic Approach to Targeted Advertising. UAI 2000: 82-88

David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie: Dependency Networks for Collaborative Filtering and Data Visualization. UAI 2000: 264-273

David Maxwell Chickering, David Heckerman: Fast Learning from Sparse Data. UAI 1999: 109-115

Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman: Learning Mixtures of DAG Models. UAI 1998: 504-513

David Maxwell Chickering, David Heckerman: Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables. Machine Learning 29(2-3): 181-212 (1997)

David Maxwell Chickering, David Heckerman, Christopher Meek: A Bayesian Approach to Learning Bayesian Networks with Local Structure. UAI 1997: 80-89

Richard E. Korf, David Maxwell Chickering: Best-First Minimax Search. Artif. Intell. 84(1-2): 299-337 (1996)

David Maxwell Chickering, Judea Pearl: A Clinician's Tool for Analyzing Non-Compliance. AAAI/IAAI, Vol. 2 1996: 1269-1276

David Maxwell Chickering: Learning Equivalence Classes of Bayesian Network Structures. UAI 1996: 150-157

David Maxwell Chickering, David Heckerman: Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network. UAI 1996: 158-168

David Maxwell Chickering, Dan Geiger, David Heckerman: On Finding a Cycle Basis with a Shortest Maximal Cycle. Inf. Process. Lett. 54(1): 55-58 (1995)

David Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. Machine Learning 20(3): 197-243 (1995)

David Maxwell Chickering: A Transformational Characterization of Equivalent Bayesian Network Structures. UAI 1995: 87-98

Richard E. Korf, David Maxwell Chickering: Best-First Minimax Search: Othello Results. AAAI 1994: 1365-1370

David Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. KDD Workshop 1994: 85-96

David Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. UAI 1994: 293-301