Publications (50)
Dependency Networks for Collaborative Filtering and Data Visualization
David Heckerman, David Maxwell Chickering, Christopher Meek +2
Dependence and Relevance: A probabilistic view
Dan Geiger, David Heckerman
Diagnosis of Multiple Faults: A Sensitivity Analysis
David Heckerman, Michael Shwe
Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network
David Maxwell Chickering, David Heckerman
A Bayesian Approach to Learning Bayesian Networks with Local Structure
David Maxwell Chickering, David Heckerman, Christopher Meek
Inference Algorithms for Similarity Networks
Dan Geiger, David Heckerman
Asymptotic Model Selection for Directed Networks with Hidden Variables
Dan Geiger, David Heckerman, Christopher Meek
Accounting for hidden common causes when inferring cause and effect from observational data
David Heckerman
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
David Heckerman, Dan Geiger, David Maxwell Chickering
Inferring Informational Goals from Free-Text Queries: A Bayesian Approach
David Heckerman, Eric J. Horvitz
A New Look at Causal Independence
David Heckerman, John S. Breese
ARMA Time-Series Modeling with Graphical Models
Bo Thiesson, David Maxwell Chickering, David Heckerman +1
Causal Independence for Knowledge Acquisition and Inference
David Heckerman
Staged Mixture Modelling and Boosting
Christopher Meek, Bo Thiesson, David Heckerman
Continuous Time Dynamic Topic Models
Chong Wang, David Blei, David Heckerman
The Myth of Modularity in Rule-Based Systems
David Heckerman, Eric J. Horvitz
Problem Formulation as the Reduction of a Decision Model
David Heckerman, Eric J. Horvitz
A Definition and Graphical Representation for Causality
David Heckerman, Ross D. Shachter
Similarity Networks for the Construction of Multiple-Faults Belief Networks
David Heckerman
Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence (1993)
David Heckerman, E. Mamdani
Large-Sample Learning of Bayesian Networks is NP-Hard
David Maxwell Chickering, Christopher Meek, David Heckerman
Empirical Analysis of Predictive Algorithms for Collaborative Filtering
John S. Breese, David Heckerman, Carl Kadie
Decision-Theoretic Troubleshooting: A Framework for Repair and Experiment
John S. Breese, David Heckerman
An Experimental Comparison of Several Clustering and Initialization Methods
Marina Meila, David Heckerman
A Bayesian Approach to Learning Causal Networks
David Heckerman
An Approximate Nonmyopic Computation for Value of Information
David Heckerman, Eric J. Horvitz, Blackford Middleton
The Role of Calculi in Uncertain Inference Systems
Michael P. Wellman, David Heckerman
A Perspective on Confidence and Its Use in Focusing Attention During Knowledge Acquisition
David Heckerman, Holly B. Jimison
Joint discovery of haplotype blocks and complex trait associations from SNP sequences
Nebojsa Jojic, Vladimir Jojic, David Heckerman
Structure and Parameter Learning for Causal Independence and Causal Interaction Models
Christopher Meek, David Heckerman
A Combination of Cutset Conditioning with Clique-Tree Propagation in the Pathfinder System
Jaap Suermondt, Gregory F. Cooper, David Heckerman
An MDP-based Recommender System
Guy Shani, Ronen I. Brafman, David Heckerman
An Axiomatic Framework for Belief Updates
David Heckerman
A powerful and efficient set test for genetic markers that handles confounders
Jennifer Listgarten, Christoph Lippert, Eun Yong Kang +3
Modular Belief Updates and Confusion about Measures of Certainty in Artificial Intelligence Research
Eric J. Horvitz, David Heckerman
Accurate Liability Estimation Improves Power in Ascertained Case Control Studies
Omer Weissbrod, Christoph Lippert, Dan Geiger +1
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
The Compilation of Decision Models
David Heckerman, John S. Breese, Eric J. Horvitz
Learning Mixtures of DAG Models
Bo Thiesson, Christopher Meek, David Maxwell Chickering +1
Advances in Probabilistic Reasoning
Dan Geiger, David Heckerman
A Decision Theoretic Approach to Targeted Advertising
David Maxwell Chickering, David Heckerman
Determining the Number of Non-Spurious Arcs in a Learned DAG Model: Investigation of a Bayesian and a Frequentist Approach
Jennifer Listgarden, David Heckerman
A Decision-Based View of Causality
David Heckerman, Ross D. Shachter
Fast Learning from Sparse Data
David Maxwell Chickering, David Heckerman
The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users
Eric J. Horvitz, John S. Breese, David Heckerman +2
Separable and transitive graphoids
Dan Geiger, David Heckerman
A Backwards View for Assessment
Ross D. Shachter, David Heckerman
Probabilistic Interpretations for MYCIN's Certainty Factors
David Heckerman
A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks
Dan Geiger, David Heckerman