David Heckerman

According to our database1, David Heckerman authored at least 178 papers between 1985 and 2018.

Collaborative distances:

Awards

ACM Fellow

ACM Fellow 2011, "For contributions to reasoning and decision-making under uncertainty.".

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepage:

On csauthors.net:

Bibliography

2018
Ensembles of Lasso Screening Rules.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Accounting for hidden common causes when inferring cause and effect from observational data.
CoRR, 2018

2016
Dependence and Relevance: A probabilistic view.
CoRR, 2016

2015
ConPADE: Genome Assembly Ploidy Estimation from Next-Generation Sequencing Data.
PLoS Computational Biology, 2015

Computational and statistical issues in personalized medicine.
ACM Crossroads, 2015

2014
Variations on undirected graphical models and their relationships.
Kybernetika, 2014

Modular Belief Updates and Confusion about Measures of Certainty in Artificial Intelligence Research.
CoRR, 2014

Literome: PubMed-scale genomic knowledge base in the cloud.
Bioinformatics, 2014

Greater power and computational efficiency for kernel-based association testing of sets of genetic variants.
Bioinformatics, 2014

2013
Proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence (1993)
CoRR, 2013

Probabilistic Interpretations for MYCIN's Certainty Factors
CoRR, 2013

A Backwards View for Assessment
CoRR, 2013

An Axiomatic Framework for Belief Updates
CoRR, 2013

The Myth of Modularity in Rule-Based Systems
CoRR, 2013

The Role of Calculi in Uncertain Inference Systems
CoRR, 2013

A Perspective on Confidence and Its Use in Focusing Attention During Knowledge Acquisition
CoRR, 2013

An Empirical Comparison of Three Inference Methods
CoRR, 2013

A Tractable Inference Algorithm for Diagnosing Multiple Diseases
CoRR, 2013

The Compilation of Decision Models
CoRR, 2013

Practical and Theoretical Advances in Knowledge Acquisition of Probabilistic Networks
CoRR, 2013

A Combination of Cutset Conditioning with Clique-Tree Propagation in the Pathfinder System
CoRR, 2013

Problem Formulation as the Reduction of a Decision Model
CoRR, 2013

Similarity Networks for the Construction of Multiple-Faults Belief Networks
CoRR, 2013

An Approximate Nonmyopic Computation for Value of Information
CoRR, 2013

Advances in Probabilistic Reasoning
CoRR, 2013

Inference Algorithms for Similarity Networks
CoRR, 2013

Causal Independence for Knowledge Acquisition and Inference
CoRR, 2013

Diagnosis of Multiple Faults: A Sensitivity Analysis
CoRR, 2013

A Decision-Based View of Causality
CoRR, 2013

Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
CoRR, 2013

A New Look at Causal Independence
CoRR, 2013

Learning Gaussian Networks
CoRR, 2013

A Bayesian Approach to Learning Causal Networks
CoRR, 2013

Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains
CoRR, 2013

A Definition and Graphical Representation for Causality
CoRR, 2013

A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks
CoRR, 2013

Asymptotic Model Selection for Directed Networks with Hidden Variables
CoRR, 2013

Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network
CoRR, 2013

Decision-Theoretic Troubleshooting: A Framework for Repair and Experiment
CoRR, 2013

Structure and Parameter Learning for Causal Independence and Causal Interaction Models
CoRR, 2013

Models and Selection Criteria for Regression and Classification
CoRR, 2013

A Bayesian Approach to Learning Bayesian Networks with Local Structure
CoRR, 2013

Learning Mixtures of DAG Models
CoRR, 2013

An Experimental Comparison of Several Clustering and Initialization Methods
CoRR, 2013

The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users
CoRR, 2013

Inferring Informational Goals from Free-Text Queries: A Bayesian Approach
CoRR, 2013

Empirical Analysis of Predictive Algorithms for Collaborative Filtering
CoRR, 2013

Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions
CoRR, 2013

Fast Learning from Sparse Data
CoRR, 2013

Dependency Networks for Collaborative Filtering and Data Visualization
CoRR, 2013

A Decision Theoretic Approach to Targeted Advertising
CoRR, 2013

An MDP-based Recommender System
CoRR, 2013

Staged Mixture Modelling and Boosting
CoRR, 2013

CFW: A Collaborative Filtering System Using Posteriors Over Weights Of Evidence
CoRR, 2013

A powerful and efficient set test for genetic markers that handles confounders.
Bioinformatics, 2013

2012
Large-Sample Learning of Bayesian Networks is NP-Hard
CoRR, 2012

ARMA Time-Series Modeling with Graphical Models
CoRR, 2012

Joint discovery of haplotype blocks and complex trait associations from SNP sequences
CoRR, 2012

Determining the Number of Non-Spurious Arcs in a Learned DAG Model: Investigation of a Bayesian and a Frequentist Approach
CoRR, 2012

Continuous Time Dynamic Topic Models
CoRR, 2012

Inferring novel associations between SNP sets and gene sets in eQTL study using sparse graphical model.
Proceedings of the ACM International Conference on Bioinformatics, 2012

2011
Correction for Hidden Confounders in the Genetic Analysis of Gene Expression (Abstract).
Proceedings of the UAI 2011, 2011

2009
PhyloDet: a scalable visualization tool for mapping multiple traits to large evolutionary trees.
Bioinformatics, 2009

Healthcare delivery in developing countries: challenges and potential solutions.
Proceedings of the Fourth Paradigm: Data-Intensive Scientific Discovery, 2009

2008
A Tutorial on Learning with Bayesian Networks.
Proceedings of the Innovations in Bayesian Networks: Theory and Applications, 2008

Comparison of Immunogen Designs That Optimize Peptide Coverage: Reply to Fischer et al.
PLoS Computational Biology, 2008

Statistical Resolution of Ambiguous HLA Typing Data.
PLoS Computational Biology, 2008

Phylogenetic Dependency Networks: Inferring Patterns of CTL Escape and Codon Covariation in HIV-1 Gag.
PLoS Computational Biology, 2008

Shift-Invariant Adaptive Double Threading: Learning MHC II-Peptide Binding.
Journal of Computational Biology, 2008

Continuous Time Dynamic Topic Models.
Proceedings of the UAI 2008, 2008

2007
Coping with Viral Diversity in HIV Vaccine Design.
PLoS Computational Biology, 2007

A Statistical Framework for Modeling HLA-Dependent T Cell Response Data.
PLoS Computational Biology, 2007

Leveraging Information Across HLA Alleles/Supertypes Improves Epitope Prediction.
Journal of Computational Biology, 2007

Spam and the ongoing battle for the inbox.
Commun. ACM, 2007

Determining the Number of Non-Spurious Arcs in a Learned DAG Model: Investigation of a Bayesian and a Frequentist Approach.
Proceedings of the UAI 2007, 2007

Shift-Invariant Adaptive Double Threading: Learning MHC II - Peptide Binding.
Proceedings of the Research in Computational Molecular Biology, 2007

2006
Considering Cost Asymmetry in Learning Classifiers.
Journal of Machine Learning Research, 2006

Leveraging Information Across HLA Alleles/Supertypes Improves Epitope Prediction.
Proceedings of the Research in Computational Molecular Biology, 2006

Learning MHC I - peptide binding.
Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

2005
An MDP-Based Recommender System.
Journal of Machine Learning Research, 2005

The First Conference on E-mail and Anti-Spam.
AI Magazine, 2005

Using epitomes to model genetic diversity: Rational design of HIV vaccines.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Large-Sample Learning of Bayesian Networks is NP-Hard.
Journal of Machine Learning Research, 2004

ARMA Time-Series Modeling with Graphical Models.
Proceedings of the UAI '04, 2004

Joint Discovery of Haplotype Blocks and Complex Trait Associations from SNP Sequences.
Proceedings of the UAI '04, 2004

Graphical models for data mining.
Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Efficient approximations for learning phylogenetic HMM models from data.
Proceedings of the Proceedings Twelfth International Conference on Intelligent Systems for Molecular Biology/Third European Conference on Computational Biology 2004, 2004

2003
Targeted Advertising on the Web with Inventory Management.
Interfaces, 2003

Model-Based Clustering and Visualization of Navigation Patterns on a Web Site.
Data Min. Knowl. Discov., 2003

Large-Sample Learning of Bayesian Networks is NP-Hard.
Proceedings of the UAI '03, 2003

Learning Bayesian Networks From Dependency Networks: A Preliminary Study.
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

Recommendation as a Stochastic Sequential Decision Problem.
Proceedings of the Thirteenth International Conference on Automated Planning and Scheduling (ICAPS 2003), 2003

2002
The Learning-Curve Sampling Method Applied to Model-Based Clustering.
Journal of Machine Learning Research, 2002

An MDP-based Recommender System.
Proceedings of the UAI '02, 2002

Staged Mixture Modelling and Boosting.
Proceedings of the UAI '02, 2002

CFW: A Collaborative Filtering System Using Posteriors over Weights of Evidence.
Proceedings of the UAI '02, 2002

Autoregressive Tree Models for Time-Series Analysis.
Proceedings of the Second SIAM International Conference on Data Mining, 2002

2001
Accelerating EM for Large Databases.
Machine Learning, 2001

An Experimental Comparison of Model-Based Clustering Methods.
Machine Learning, 2001

Statistical Models for Data Mining.
Data Min. Knowl. Discov., 2001

Separating Appearance from Deformation.
ICCV, 2001

The Learning Curve Method Applied to Clustering.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

Learning mixtures of smooth, nonuniform deformation models for probabilistic image matching.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
A comparison of scientific and engineering criteria for Bayesian model selection.
Statistics and Computing, 2000

Dependency Networks for Inference, Collaborative Filtering, and Data Visualization.
Journal of Machine Learning Research, 2000

Dependency Networks for Collaborative Filtering and Data Visualization.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

A Decision Theoretic Approach to Targeted Advertising.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Targeted advertising with inventory management.
EC, 2000

Visualization of navigation patterns on a Web site using model-based clustering.
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

1999
Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

Fast Learning from Sparse Data.
Proceedings of the UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence, Stockholm, Sweden, July 30, 1999

On the geometry of DAG models with hidden variables.
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

1998
Probabilistic relevance relations.
IEEE Trans. Systems, Man, and Cybernetics, Part A, 1998

Learning Mixtures of DAG Models.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

An Experimental Comparison of Several Clustering and Initialization Methods.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Inferring Informational Goals from Free-Text Queries: A Bayesian Approach.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Empirical Analysis of Predictive Algorithms for Collaborative Filtering.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

1997
Probabilistic Independence Networks for Hidden Markov Probability Models.
Neural Computation, 1997

Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables.
Machine Learning, 1997

Bayesian Networks for Data Mining.
Data Min. Knowl. Discov., 1997

Structure and Parameter Learning for Causal Independence and Causal Interaction Models.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Models and Selection Criteria for Regression and Classification.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

A Bayesian Approach to Learning Bayesian Networks with Local Structure.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Challenge: What is the Impact of Bayesian Networks on Learning?
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

1996
Causal independence for probability assessment and inference using Bayesian networks.
IEEE Trans. Systems, Man, and Cybernetics, Part A, 1996

Decision-theoretic case-based reasoning.
IEEE Trans. Systems, Man, and Cybernetics, Part A, 1996

Knowledge Representation and Inference in Similarity Networks and Bayesian Multinets.
Artif. Intell., 1996

Asymptotic Model Selection for Directed Networks with Hidden Variables.
Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network.
Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

Decision-Theoretic Troubleshooting: A Framework for Repair and Experiment.
Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

Bayesian Networks for Knowledge Discovery.
Advances in Knowledge Discovery and Data Mining, 1996

Probabilistic and Bayesian Representations of Uncertainty in Information Systems: A Pragmatic Introduction.
Uncertainty Management in Information Systems, 1996

1995
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data.
Machine Learning, 1995

Decision-Theoretic Foundations for Causal Reasoning.
J. Artif. Intell. Res., 1995

On Finding a Cycle Basis with a Shortest Maximal Cycle.
Inf. Process. Lett., 1995

Editorial: real-world applications of uncertain reasoning.
Int. J. Hum.-Comput. Stud., 1995

Decision-Theoretic Foundations for Causal Reasoning.
CoRR, 1995

Real-World Applications of Bayesian Networks - Introduction.
Commun. ACM, 1995

Bayesian Networks.
Commun. ACM, 1995

Decision-Theoretic Troubleshooting.
Commun. ACM, 1995

A Definition and Graphical Representation for Causality.
Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains.
Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

A Bayesian Approach to Learning Causal Networks.
Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks.
Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

Learning With Bayesian Networks (Abstract).
Proceedings of the Machine Learning, 1995

1994
A Decision-based View of Causality.
Proceedings of the UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, 1994

Learning Bayesian Networks: The Combination of Knowledge and Statistical Data.
Proceedings of the UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, 1994

A New Look at Causal Independence.
Proceedings of the UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, 1994

Learning Gaussian Networks.
Proceedings of the UAI '94: Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, 1994

Learning Bayesian Networks: The Combination of Knowledge and Statistical Data.
Proceedings of the Knowledge Discovery in Databases: Papers from the 1994 AAAI Workshop, 1994

1993
An Approximate Nonmyopic Computation for Value of Information.
IEEE Trans. Pattern Anal. Mach. Intell., 1993

Diagnosis of Multiple Faults: A Sensitivity Analysis.
Proceedings of the UAI '93: Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence, 1993

Causal Independence for Knowledge Acquisition and Inference.
Proceedings of the UAI '93: Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence, 1993

Inference Algorithms for Similarity Networks.
Proceedings of the UAI '93: Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence, 1993

1992
From certainty factors to belief networks.
Artificial Intelligence in Medicine, 1992

1991
An Approximate Nonmyopic Computation for Value of Information.
Proceedings of the UAI '91: Proceedings of the Seventh Annual Conference on Uncertainty in Artificial Intelligence, 1991

Advances in Probabilistic Reasoning.
Proceedings of the UAI '91: Proceedings of the Seventh Annual Conference on Uncertainty in Artificial Intelligence, 1991

Probabilistic similarity networks.
ACM Doctoral dissertation awards, MIT Press, ISBN: 978-0-262-08206-8, 1991

1990
Probabilistic similarity networks.
Networks, 1990

A combination of cutset conditioning with clique-tree propagation in the Pathfinder system.
Proceedings of the UAI '90: Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence, 1990

Problem formulation as the reduction of a decision model.
Proceedings of the UAI '90: Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence, 1990

Similarity networks for the construction of multiple-faults belief networks.
Proceedings of the UAI '90: Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence, 1990

separable and transitive graphoids.
Proceedings of the UAI '90: Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence, 1990

1989
A Tractable Inference Algorithm for Diagnosing Multiple Diseases.
Proceedings of the UAI '89: Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence, 1989

Reflection and Action Under Scarce Resources: Theoretical Principles and Empirical Study.
Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

1988
A perspective on confidence and its use in focusing attention during knowledge acquisition.
Int. J. Approx. Reasoning, 1988

An empirical comparison of three inference methods.
Proceedings of the UAI '88: Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence, 1988

1987
Thinking Backward for Knowledge Acquisition.
AI Magazine, 1987

A Bayesian Perspective on Confidence.
Proceedings of the UAI '87: Proceedings of the Third Annual Conference on Uncertainty in Artificial Intelligence, 1987

On the Expressiveness of Rule-based Systems for Reasoning with Uncertainty.
Proceedings of the 6th National Conference on Artificial Intelligence. Seattle, 1987

1986
A backwards view for assessment.
Proceedings of the UAI '86: Proceedings of the Second Annual Conference on Uncertainty in Artificial Intelligence, 1986

The myth of modularity in rule-based systems for reasoning with uncertainty.
Proceedings of the UAI '86: Proceedings of the Second Annual Conference on Uncertainty in Artificial Intelligence, 1986

An axiomatic framework for belief updates.
Proceedings of the UAI '86: Proceedings of the Second Annual Conference on Uncertainty in Artificial Intelligence, 1986

A Framework for Comparing Alternative Formalisms for Plausible Reasoning.
Proceedings of the 5th National Conference on Artificial Intelligence. Philadelphia, 1986

1985
The Inconsistent Use of Measures of Certainty in Artificial Intelligence Research.
Proceedings of the UAI '85: Proceedings of the First Annual Conference on Uncertainty in Artificial Intelligence, 1985

Probabilistic Interpretation for MYCIN's Certainty Factors.
Proceedings of the UAI '85: Proceedings of the First Annual Conference on Uncertainty in Artificial Intelligence, 1985


  Loading...