Christopher Meek

Machine Learning Department, Microsoft Research

	2013
i24		David Maxwell Chickering, Christopher Meek: Finding Optimal Bayesian Networks. CoRR abs/1301.0561 (2013)
i23		Dan Geiger, Christopher Meek, Bernd Sturmfels: Factorization of Discrete Probability Distributions. CoRR abs/1301.0568 (2013)
i22		Carl Myers Kadie, Christopher Meek, David Heckerman: CFW: A Collaborative Filtering System Using Posteriors Over Weights Of Evidence. CoRR abs/1301.0575 (2013)
i21		Christopher Meek, Bo Thiesson, David Heckerman: Staged Mixture Modelling and Boosting. CoRR abs/1301.0586 (2013)
i20		Andrew Zimdars, David Maxwell Chickering, Christopher Meek: Using Temporal Data for Making Recommendations. CoRR abs/1301.2320 (2013)
i19		Ann Becker, Dan Geiger, Christopher Meek: Perfect Tree-Like Markovian Distributions. CoRR abs/1301.3834 (2013)
i18		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)
i17		Christopher Meek, Uffe Kjærulff: Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (2003). CoRR abs/1301.4606 (2013)
i16		Dan Geiger, Christopher Meek: Quantifier Elimination for Statistical Problems. CoRR abs/1301.6698 (2013)
i15		Dan Geiger, Christopher Meek: Graphical Models and Exponential Families. CoRR abs/1301.7376 (2013)
i14		Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman: Learning Mixtures of DAG Models. CoRR abs/1301.7415 (2013)
i13		David Maxwell Chickering, David Heckerman, Christopher Meek: A Bayesian Approach to Learning Bayesian Networks with Local Structure. CoRR abs/1302.1528 (2013)
i12		David Heckerman, Christopher Meek: Models and Selection Criteria for Regression and Classification. CoRR abs/1302.1545 (2013)
i11		Christopher Meek, David Heckerman: Structure and Parameter Learning for Causal Independence and Causal Interaction Models. CoRR abs/1302.1561 (2013)
i10		Dan Geiger, David Heckerman, Christopher Meek: Asymptotic Model Selection for Directed Networks with Hidden Variables. CoRR abs/1302.3580 (2013)
i9		Christopher Meek: Causal Inference and Causal Explanation with Background Knowledge. CoRR abs/1302.4972 (2013)
i8		Christopher Meek: Strong Completeness and Faithfulness in Bayesian Networks. CoRR abs/1302.4973 (2013)
i7		Peter Spirtes, Christopher Meek, Thomas S. Richardson: Causal Inference in the Presence of Latent Variables and Selection Bias. CoRR abs/1302.4983 (2013)
	2012
c49		Geoffrey Zweig, John C. Platt, Christopher Meek, Christopher J. C. Burges, Ainur Yessenalina, Qiang Liu: Computational Approaches to Sentence Completion. ACL (1) 2012: 601-610
i6		Ydo Wexler, Christopher Meek: Inference for Multiplicative Models. CoRR abs/1206.3296 (2012)
i5		Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek: ARMA Time-Series Modeling with Graphical Models. CoRR abs/1207.4162 (2012)
i4		David Maxwell Chickering, Christopher Meek, David Heckerman: Large-Sample Learning of Bayesian Networks is NP-Hard. CoRR abs/1212.2468 (2012)
i3		Christopher Meek, David Maxwell Chickering: Practically Perfect. CoRR abs/1212.2503 (2012)
	2011
j15		Guy Shani, Asela Gunawardana, Christopher Meek: Unsupervised hierarchical probabilistic segmentation of discrete events. Intell. Data Anal. 15(4): 483-501 (2011)
c48		Darko Kirovski, Christopher Meek: Tunneled TLS for multi-factor authentication. Digital Rights Management Workshop 2011: 31-40
c47		Asela Gunawardana, Christopher Meek, Puyang Xu: A Model for Temporal Dependencies in Event Streams. NIPS 2011: 1962-1970
i2		Christopher Meek: Finding a Path is Harder than Finding a Tree. CoRR abs/1106.1799 (2011)
i1		Greg Linden, Christopher Meek, Max Chickering: The Pollution Effect: Optimizing Keyword Auctions by Favoring Relevant Advertising. CoRR abs/1109.6263 (2011)
	2010
j14		Sivan Bercovici, Christopher Meek, Ydo Wexler, Dan Geiger: Estimating genome-wide IBD sharing from SNP data via an efficient hidden Markov model of LD with application to gene mapping. Bioinformatics [ISMB] 26(12): 175-182 (2010)
c46		Asela Gunawardana, Tim Paek, Christopher Meek: Usability guided key-target resizing for soft keyboards. IUI 2010: 111-118
c45		Jim C. Huang, Nebojsa Jojic, Christopher Meek: Exact inference and learning for cumulative distribution functions on loopy graphs. NIPS 2010: 874-882
	2009
j13		Dan Geiger, Christopher Meek, Ydo Wexler: Speeding up HMM algorithms for genetic linkage analysis via chain reductions of the state space. Bioinformatics 25(12) (2009)
j12		Chong Wang, Bo Thiesson, Christopher Meek, David M. Blei: Markov Topic Models. Journal of Machine Learning Research - Proceedings Track 5: 583-590 (2009)
c44		Guy Shani, Christopher Meek, Asela Gunawardana: Hierarchical Probabilistic Segmentation of Discrete Events. ICDM 2009: 974-979
c43		Guy Shani, Christopher Meek, Tim Paek, Bo Thiesson, Gina Danielle Venolia: Searching large indexes on tiny devices: optimizing binary search with character pinning. IUI 2009: 257-266
c42		Guy Shani, Christopher Meek: Improving Existing Fault Recovery Policies. NIPS 2009: 1642-1650
c41		Asela Gunawardana, Christopher Meek: A unified approach to building hybrid recommender systems. RecSys 2009: 117-124
	2008
c40		Ece Kamar, Eric Horvitz, Christopher Meek: Mobile opportunistic commerce: mechanisms, architecture, and application. AAMAS (2) 2008: 1087-1094
c39		Ming-wei Chang, Wen-tau Yih, Christopher Meek: Partitioned logistic regression for spam filtering. KDD 2008: 97-105
c38		Ydo Wexler, Christopher Meek: MAS: a multiplicative approximation scheme for probabilistic inference. NIPS 2008: 1761-1768
c37		Asela Gunawardana, Christopher Meek: Tied boltzmann machines for cold start recommendations. RecSys 2008: 19-26
c36		Guy Shani, David Maxwell Chickering, Christopher Meek: Mining recommendations from the web. RecSys 2008: 35-42
c35		Ydo Wexler, Christopher Meek: Inference for Multiplicative Models. UAI 2008: 595-602
	2007
c34		Hila Becker, Christopher Meek, David Maxwell Chickering: Modeling Contextual Factors of Click Rates. AAAI 2007: 1310-1315
c33		Wen-tau Yih, Christopher Meek: Improving Similarity Measures for Short Segments of Text. AAAI 2007: 1489-1494
c32		Donald Metzler, Susan T. Dumais, Christopher Meek: Similarity Measures for Short Segments of Text. ECIR 2007: 16-27
c31		Tim Paek, Yun-Cheng Ju, Christopher Meek: People watcher: a game for eliciting human-transcribed data for automated directory assistance. INTERSPEECH 2007: 1322-1325
	2006
j11		David Maxwell Chickering, Christopher Meek: On the incompatibility of faithfulness and monotone DAG faithfulness. Artif. Intell. 170(8-9): 653-666 (2006)
j10		Michail Vlachos, Philip S. Yu, Vittorio Castelli, Christopher Meek: Structural Periodic Measures for Time-Series Data. Data Min. Knowl. Discov. 12(1): 1-28 (2006)
j9		Dan Geiger, Christopher Meek, Ydo Wexler: A Variational Inference Procedure Allowing Internal Structure for Overlapping Clusters and Deterministic Constraints. J. Artif. Intell. Res. (JAIR) 27: 1-23 (2006)
j8		Serkan Hosten, Christopher Meek: Preface. J. Symb. Comput. 41(2): 123-124 (2006)
	2005
c30		Daniel Lowd, Christopher Meek: Good Word Attacks on Statistical Spam Filters. CEAS 2005
c29		Daniel Lowd, Christopher Meek: Adversarial learning. KDD 2005: 641-647
c28		Nebojsa Jojic, Vladimir Jojic, Brendan J. Frey, Christopher Meek, David Heckerman: Using epitomes to model genetic diversity: Rational design of HIV vaccines. NIPS 2005
	2004
j7		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)
c27		Vladimir Jojic, Nebojsa Jojic, Christopher Meek, Dan Geiger, Adam C. Siepel, David Haussler, David Heckerman: Efficient approximations for learning phylogenetic HMM models from data. ISMB/ECCB (Supplement of Bioinformatics) 2004: 161-168
c26		Michail Vlachos, Christopher Meek, Zografoula Vagena, Dimitrios Gunopulos: Identifying Similarities, Periodicities and Bursts for Online Search Queries. SIGMOD Conference 2004: 131-142
c25		Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek: ARMA Time-Series Modeling with Graphical Models. UAI 2004: 552-560
	2003
j6		Igor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White: Model-Based Clustering and Visualization of Navigation Patterns on a Web Site. Data Min. Knowl. Discov. 7(4): 399-424 (2003)
c24		David Maxwell Chickering, Christopher Meek, David Heckerman: Large-Sample Learning of Bayesian Networks is NP-Hard. UAI 2003: 124-133
c23		Christopher Meek, David Maxwell Chickering: Practically Perfect. UAI 2003: 411-416
e1		Christopher Meek, Uffe Kjærulff (Eds.): UAI '03, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence, Acapulco, Mexico, August 7-10 2003. Morgan Kaufmann 2003, isbn 0-127-05664-5
	2002
j5		Christopher Meek, Bo Thiesson, David Heckerman: The Learning-Curve Sampling Method Applied to Model-Based Clustering. Journal of Machine Learning Research 2: 397-418 (2002)
c22		Christopher Meek, David Maxwell Chickering, David Heckerman: Autoregressive Tree Models for Time-Series Analysis. SDM 2002
c21		David Maxwell Chickering, Christopher Meek: Finding Optimal Bayesian Networks. UAI 2002: 94-102
c20		Dan Geiger, Christopher Meek, Bernd Sturmfels: Factorization of Discrete Probability Distributions. UAI 2002: 162-169
c19		Carl Myers Kadie, Christopher Meek, David Heckerman: CFW: A Collaborative Filtering System Using Posteriors over Weights of Evidence. UAI 2002: 242-250
c18		Christopher Meek, Bo Thiesson, David Heckerman: Staged Mixture Modelling and Boosting. UAI 2002: 335-343
	2001
j4		Christopher Meek: Finding a Path is Harder than Finding a Tree. J. Artif. Intell. Res. (JAIR) 15: 383-389 (2001)
j3		Bo Thiesson, Christopher Meek, David Heckerman: Accelerating EM for Large Databases. Machine Learning 45(3): 279-299 (2001)
c17		David Maxwell Chickering, Christopher Meek, Robert Rounthwaite: Efficient Determination of Dynamic Split Points in a Decision Tree. ICDM 2001: 91-98
c16		Andrew Zimdars, David Maxwell Chickering, Christopher Meek: Using Temporal Data for Making Recommendations. UAI 2001: 580-588
	2000
j2		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)
c15		Jake D. Brutlag, Christopher Meek: Challenges of the Email Domain for Text Classification. ICML 2000: 103-110
c14		Heikki Mannila, Christopher Meek: Global partial orders from sequential data. KDD 2000: 161-168
c13		Igor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White: Visualization of navigation patterns on a Web site using model-based clustering. KDD 2000: 280-284
c12		Ann Becker, Dan Geiger, Christopher Meek: Perfect Tree-like Markovian Distributions. UAI 2000: 19-23
c11		David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie: Dependency Networks for Collaborative Filtering and Data Visualization. UAI 2000: 264-273
	1999
c10		Dan Geiger, Christopher Meek: Quantifier Elimination for Statistical Problems. UAI 1999: 226-235
	1998
c9		Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman: Learning Mixtures of DAG Models. UAI 1998: 504-513
	1997
j1		Gregory F. Cooper, Constantin F. Aliferis, Richard Ambrosino, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Clark Glymour, Geoffrey J. Gordon, Barbara H. Hanusa, Janine E. Janosky, Christopher Meek, Tom M. Mitchell, Thomas S. Richardson, Peter Spirtes: An evaluation of machine-learning methods for predicting pneumonia mortality. Artificial Intelligence in Medicine 9(2): 107-138 (1997)
c8		David Maxwell Chickering, David Heckerman, Christopher Meek: A Bayesian Approach to Learning Bayesian Networks with Local Structure. UAI 1997: 80-89
c7		David Heckerman, Christopher Meek: Models and Selection Criteria for Regression and Classification. UAI 1997: 223-228
c6		Christopher Meek, David Heckerman: Structure and Parameter Learning for Causal Independence and Causal Interaction Models. UAI 1997: 366-375
	1996
c5		Dan Geiger, David Heckerman, Christopher Meek: Asymptotic Model Selection for Directed Networks with Hidden Variables. UAI 1996: 283-290
	1995
c4		Peter Spirtes, Christopher Meek: Learning Bayesian Networks with Discrete Variables from Data. KDD 1995: 294-299
c3		Christopher Meek: Causal inference and causal explanation with background knowledge. UAI 1995: 403-410
c2		Christopher Meek: Strong completeness and faithfulness in Bayesian networks. UAI 1995: 411-418
c1		Peter Spirtes, Christopher Meek, Thomas S. Richardson: Causal Inference in the Presence of Latent Variables and Selection Bias. UAI 1995: 499-506

Coauthor Index

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