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David Heckerman
Microsoft Research
Contact Information
Webpage :
http://research.microsoft.com/~heckerman
Email :
heckerma@microsoft.com
Phone : 425 935 26
Fax : 425 936 73
Mailing Address
One Microsoft Way
Redmond, WA 98052
USA
Publications in UAI
UAI-1990
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Problem Formulation as the Reduction of a Decision Model
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Similarity Networks for the Construction of Multiple-Fault Belief Networks
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A Combination of Cutset Conditioning with Clique-Tree Propagation in the Pathfinder System
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Separable and Transitive Graphoids
UAI-1989
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A Tractable Inference Algorithm for Diagnosing Multiple Diseases
UAI-1988
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An Empirical Comparison of Three Inference Methods
UAI-1987
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A Bayesian Perspective on Confidence
UAI-1986
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A Backwards View for Assessment
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An Axiomatic Framework for Belief Updates
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The Myth of Modularity In Rule-Based Systems for Reasoning with Uncertainty
UAI-1985
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Probabilistic Interpretations for MYCIN's Certainty Factors
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The Inconsistent Use of Measures of Certainty in Artificial Intelligence Research
UAI-2011
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Correction for Hidden Confounders in the Genetic Analysis of Gene Expression
UAI-2008
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Continuous Time Dynamic Topic Models
UAI-2007
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Determining the Number of Non-Spurious Arcs in a Learned DAG Model: Investigation of a Bayesian and a Frequentist Approach
UAI-2004
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ARMA Time-Series Modeling with Graphical Models
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Joint discovery of haplotype blocks and complex trait associations from SNP sequences
UAI-2003
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Large-Sample Learning of Bayesian Networks is NP-Hard
UAI-2002
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Staged Mixture Modelling and Boosting
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An MDP-based Recommender System
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CFW: A Collaborative Filtering System Using Posteriors Over Weights Of Evidence
UAI-2000
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A Decision Theoretic Approach to Targeted Advertising
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Dependency Networks for Collaborative Filtering and Data Visualization
UAI-1999
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Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions
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Fast Learning from Sparse Data
UAI-1998
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The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users
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Empirical Analysis of Predictive Algorithms for Collaborative Filtering
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An Experimental Comparison of Several Clustering and Initialization Methods
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Inferring Informational Goals from Free-Text Queries: A Bayesian Approach
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Learning Mixtures of DAG Models
UAI-1997
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A Bayesian Approach to Learning Bayesian Networks with Local Structure
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Models and Selection Criteria for Regression and Classification
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Structure and Parameter Learning for Causal Independence and Causal Interaction Models
UAI-1996
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Decision-Theoretic Troubleshooting: A Framework for Repair and Experiment
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Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network
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Asymptotic Model Selection for Directed Networks with Hidden Variables
UAI-1995
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A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks
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A Bayesian Approach to Learning Causal Networks
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A Definition and Graphical Representation for Causality
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Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains
UAI-1994
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Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
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Learning Gaussian Networks
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A Decision-Based View of Causality
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A New Look at Causal Independence
UAI-1993
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Causal Independence for Knowledge Acquisition and Inference
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Inference Algorithms for Similarity Networks
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Diagnosis of Multiple Faults: A Sensitivity Analysis
UAI-1991
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An Approximate Nonmyopic Computation for Value of Information
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Advances in Probabilistic Reasoning
UAI-1990
::
Problem Formulation as the Reduction of a Decision Model
::
Similarity Networks for the Construction of Multiple-Faults Belief Networks
::
A Combination of Cutset Conditioning with Clique-Tree Propagation in the Pathfinder System
::
Separable and transitive graphoids
UAI-1989
::
A Tractable Inference Algorithm for Diagnosing Multiple Diseases
::
The Compilation of Decision Models
UAI-1988
::
An Empirical Comparison of Three Inference Methods
UAI-1987
::
The Role of Calculi in Uncertain Inference Systems
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A Perspective on Confidence and Its Use in Focusing Attention During Knowledge Acquisition
UAI-1986
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A Backwards View for Assessment
::
An Axiomatic Framework for Belief Updates
::
The Myth of Modularity in Rule-Based Systems
UAI-1985
::
Probabilistic Interpretations for MYCIN's Certainty Factors
::
Modular Belief Updates and Confusion about Measures of Certainty in Artificial Intelligence Research
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