Publications (29)
ARMA Time-Series Modeling with Graphical Models
Bo Thiesson, David Maxwell Chickering, David Heckerman +1
Staged Mixture Modelling and Boosting
Christopher Meek, Bo Thiesson, David Heckerman
Causal Inference and Causal Explanation with Background Knowledge
Christopher Meek
Analysis of a Design Pattern for Teaching with Features and Labels
Christopher Meek, Patrice Simard, Xiaojin Zhu
On the toric algebra of graphical models
Dan Geiger, Christopher Meek, Bernd Sturmfels
Large-Sample Learning of Bayesian Networks is NP-Hard
David Maxwell Chickering, Christopher Meek, David Heckerman
Strong Completeness and Faithfulness in Bayesian Networks
Christopher Meek
The Pollution Effect: Optimizing Keyword Auctions by Favoring Relevant Advertising
Greg Linden, Christopher Meek, Max Chickering
Using Temporal Data for Making Recommendations
Andrew Zimdars, David Maxwell Chickering, Christopher Meek
Factorization of Discrete Probability Distributions
Dan Geiger, Christopher Meek, Bernd Sturmfels
Structure and Parameter Learning for Causal Independence and Causal Interaction Models
Christopher Meek, David Heckerman
CFW: A Collaborative Filtering System Using Posteriors Over Weights Of Evidence
Carl Kadie, Christopher Meek, David Heckerman
Models and Selection Criteria for Regression and Classification
David Heckerman, Christopher Meek
A Characterization of Prediction Errors
Christopher Meek
Learning Mixtures of DAG Models
Bo Thiesson, Christopher Meek, David Maxwell Chickering +1
Quantifier Elimination for Statistical Problems
Dan Geiger, Christopher Meek
Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence (2003)
Christopher Meek, Uffe Kjaerulff
Practically Perfect
Christopher Meek, David Maxwell Chickering
Inference for Multiplicative Models
Ydo Wexler, Christopher Meek
Graphical Models and Exponential Families
Dan Geiger, Christopher Meek
Regularized Minimax Conditional Entropy for Crowdsourcing
Dengyong Zhou, Qiang Liu, John C. Platt +2
Machine Teaching: A New Paradigm for Building Machine Learning Systems
Patrice Y. Simard, Saleema Amershi, David M. Chickering +8
Causal Inference in the Presence of Latent Variables and Selection Bias
Peter L. Spirtes, Christopher Meek, Thomas S. Richardson
Dependency Networks for Collaborative Filtering and Data Visualization
David Heckerman, David Maxwell Chickering, Christopher Meek +2
Perfect Tree-Like Markovian Distributions
Ann Becker, Dan Geiger, Christopher Meek
A Bayesian Approach to Learning Bayesian Networks with Local Structure
David Maxwell Chickering, David Heckerman, Christopher Meek
Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks Using a Polynomial Number of Score Evaluations
David Maxwell Chickering, Christopher Meek
Asymptotic Model Selection for Directed Networks with Hidden Variables
Dan Geiger, David Heckerman, Christopher Meek
Finding Optimal Bayesian Networks
David Maxwell Chickering, Christopher Meek