2009 | ||
---|---|---|
51 | EE | 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 |
2008 | ||
50 | EE | Ming-wei Chang, Wen-tau Yih, Christopher Meek: Partitioned logistic regression for spam filtering. KDD 2008: 97-105 |
49 | EE | Ydo Wexler, Christopher Meek: MAS: a multiplicative approximation scheme for probabilistic inference. NIPS 2008: 1761-1768 |
48 | EE | Asela Gunawardana, Christopher Meek: Tied boltzmann machines for cold start recommendations. RecSys 2008: 19-26 |
47 | EE | Guy Shani, David Maxwell Chickering, Christopher Meek: Mining recommendations from the web. RecSys 2008: 35-42 |
46 | EE | Ydo Wexler, Christopher Meek: Inference for Multiplicative Models. UAI 2008: 595-602 |
2007 | ||
45 | Hila Becker, Christopher Meek, David Maxwell Chickering: Modeling Contextual Factors of Click Rates. AAAI 2007: 1310-1315 | |
44 | Wen-tau Yih, Christopher Meek: Improving Similarity Measures for Short Segments of Text. AAAI 2007: 1489-1494 | |
43 | EE | Donald Metzler, Susan T. Dumais, Christopher Meek: Similarity Measures for Short Segments of Text. ECIR 2007: 16-27 |
2006 | ||
42 | EE | David Maxwell Chickering, Christopher Meek: On the incompatibility of faithfulness and monotone DAG faithfulness. Artif. Intell. 170(8-9): 653-666 (2006) |
41 | EE | 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) |
40 | EE | 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) |
39 | EE | Serkan Hosten, Christopher Meek: Preface. J. Symb. Comput. 41(2): 123-124 (2006) |
2005 | ||
38 | EE | Daniel Lowd, Christopher Meek: Good Word Attacks on Statistical Spam Filters. CEAS 2005 |
37 | EE | Daniel Lowd, Christopher Meek: Adversarial learning. KDD 2005: 641-647 |
36 | EE | 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 | ||
35 | EE | 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 |
34 | EE | Michail Vlachos, Christopher Meek, Zografoula Vagena, Dimitrios Gunopulos: Identifying Similarities, Periodicities and Bursts for Online Search Queries. SIGMOD Conference 2004: 131-142 |
33 | EE | Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek: ARMA Time-Series Modeling with Graphical Models. UAI 2004: 552-560 |
32 | EE | 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) |
2003 | ||
31 | Christopher Meek, Uffe Kjærulff: UAI '03, Proceedings of the 19th Conference in Uncertainty in Artificial Intelligence, August 7-10 2003, Acapulco, Mexico Morgan Kaufmann 2003 | |
30 | David Maxwell Chickering, Christopher Meek, David Heckerman: Large-Sample Learning of Bayesian Networks is NP-Hard. UAI 2003: 124-133 | |
29 | Christopher Meek, David Maxwell Chickering: Practically Perfect. UAI 2003: 411-416 | |
28 | EE | 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) |
2002 | ||
27 | EE | Christopher Meek, David Maxwell Chickering, David Heckerman: Autoregressive Tree Models for Time-Series Analysis. SDM 2002 |
26 | Dan Geiger, Christopher Meek, Bernd Sturmfels: Factorization of Discrete Probability Distributions. UAI 2002: 162-169 | |
25 | Carl Myers Kadie, Christopher Meek, David Heckerman: CFW: A Collaborative Filtering System Using Posteriors over Weights of Evidence. UAI 2002: 242-250 | |
24 | Christopher Meek, Bo Thiesson, David Heckerman: Staged Mixture Modelling and Boosting. UAI 2002: 335-343 | |
23 | David Maxwell Chickering, Christopher Meek: Finding Optimal Bayesian Networks. UAI 2002: 94-102 | |
22 | EE | 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) |
2001 | ||
21 | EE | David Maxwell Chickering, Christopher Meek, Robert Rounthwaite: Efficient Determination of Dynamic Split Points in a Decision Tree. ICDM 2001: 91-98 |
20 | EE | Andrew Zimdars, David Maxwell Chickering, Christopher Meek: Using Temporal Data for Making Recommendations. UAI 2001: 580-588 |
19 | EE | Christopher Meek: Finding a Path is Harder than Finding a Tree. J. Artif. Intell. Res. (JAIR) 15: 383-389 (2001) |
18 | Bo Thiesson, Christopher Meek, David Heckerman: Accelerating EM for Large Databases. Machine Learning 45(3): 279-299 (2001) | |
2000 | ||
17 | Jake D. Brutlag, Christopher Meek: Challenges of the Email Domain for Text Classification. ICML 2000: 103-110 | |
16 | EE | Heikki Mannila, Christopher Meek: Global partial orders from sequential data. KDD 2000: 161-168 |
15 | EE | 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 |
14 | EE | Ann Becker, Dan Geiger, Christopher Meek: Perfect Tree-like Markovian Distributions. UAI 2000: 19-23 |
13 | EE | David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie: Dependency Networks for Collaborative Filtering and Data Visualization. UAI 2000: 264-273 |
12 | EE | 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) |
1999 | ||
11 | EE | Dan Geiger, Christopher Meek: Quantifier Elimination for Statistical Problems. UAI 1999: 226-235 |
1998 | ||
10 | EE | Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman: Learning Mixtures of DAG Models. UAI 1998: 504-513 |
1997 | ||
9 | EE | David Heckerman, Christopher Meek: Models and Selection Criteria for Regression and Classification. UAI 1997: 223-228 |
8 | EE | Christopher Meek, David Heckerman: Structure and Parameter Learning for Causal Independence and Causal Interaction Models. UAI 1997: 366-375 |
7 | EE | David Maxwell Chickering, David Heckerman, Christopher Meek: A Bayesian Approach to Learning Bayesian Networks with Local Structure. UAI 1997: 80-89 |
6 | Gregory F. Cooper, Constantin F. Aliferis, R. Ambrosino, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Clark Glymour, G. Gordon, B. H. Hanusa, Janine E. Janosky, Christopher Meek, Tom M. Mitchell, Thomas Richardson, Peter Spirtes: An evaluation of machine-learning methods for predicting pneumonia mortality. Artificial Intelligence in Medicine 9(2): 107-138 (1997) | |
1996 | ||
5 | EE | Dan Geiger, David Heckerman, Christopher Meek: Asymptotic Model Selection for Directed Networks with Hidden Variables. UAI 1996: 283-290 |
1995 | ||
4 | Peter Spirtes, Christopher Meek: Learning Bayesian Networks with Discrete Variables from Data. KDD 1995: 294-299 | |
3 | EE | Christopher Meek: Causal inference and causal explanation with background knowledge. UAI 1995: 403-410 |
2 | EE | Christopher Meek: Strong completeness and faithfulness in Bayesian networks. UAI 1995: 411-418 |
1 | EE | Peter Spirtes, Christopher Meek, Thomas Richardson: Causal Inference in the Presence of Latent Variables and Selection Bias. UAI 1995: 499-506 |