David Heckerman

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

Venues

Active years

1985–2024

Best venue rank

Where they publish

Papers

73 indexed papers, newest first.

Year	Venue	Title	Authors
2024	ICML	Multiply-Robust Causal Change Attribution.	Victor Quintas-Martinez, Mohammad Taha Bahadori, Eduardo Santiago, Jeff Mu, David Heckerman
2022	ICML	End-to-End Balancing for Causal Continuous Treatment-Effect Estimation.	Mohammad Taha Bahadori, Eric Tchetgen Tchetgen, David Heckerman
2021	ICLR	Debiasing Concept-based Explanations with Causal Analysis.	Mohammad Taha Bahadori, David Heckerman
2019	KDD	Exploiting High Dimensionality in Big Data.	David Heckerman
2011	UAI	Correction for Hidden Confounders in the Genetic Analysis of Gene Expression (Abstract).	Jennifer Listgarten, Carl Myers Kadie, Eric E. Schadt, David Heckerman
2008	UAI	Continuous Time Dynamic Topic Models.	Chong Wang, David M. Blei, David Heckerman
2007	RECOMB	Shift-Invariant Adaptive Double Threading: Learning MHC II - Peptide Binding.	Noah Zaitlen, Manuel Reyes-Gomez, David Heckerman, Nebojsa Jojic
2007	UAI	Determining the Number of Non-Spurious Arcs in a Learned DAG Model: Investigation of a Bayesian and a Frequentist Approach.	Jennifer Listgarten, David Heckerman
2006	ISMB	Learning MHC I - peptide binding.	Nebojsa Jojic, Manuel Reyes-Gomez, David Heckerman, Carl Myers Kadie, Ora Schueler-Furman
2006	RECOMB	Leveraging Information Across HLA Alleles/Supertypes Improves Epitope Prediction.	David Heckerman, Carl Myers Kadie, Jennifer Listgarten
2005	AISTATS	On the Path to an Ideal ROC Curve: Considering Cost Asymmetry in Learning Classifiers.	Francis R. Bach, David Heckerman, Eric Horvitz
2004	ISMB	Efficient approximations for learning phylogenetic HMM models from data.	Vladimir Jojic, Nebojsa Jojic, Christopher Meek, Dan Geiger, Adam C. Siepel, David Haussler, David Heckerman
2004	KDD	Graphical models for data mining.	David Heckerman
2004	UAI	Joint Discovery of Haplotype Blocks and Complex Trait Associations from SNP Sequences.	Nebojsa Jojic, Vladimir Jojic, David Heckerman
2004	UAI	ARMA Time-Series Modeling with Graphical Models.	Bo Thiesson, David Maxwell Chickering, David Heckerman, Christopher Meek
2003	AISTATS	Learning Bayesian Networks From Dependency Networks: A Preliminary Study.	Geoff Hulten, David Maxwell Chickering, David Heckerman
2003	UAI	Large-Sample Learning of Bayesian Networks is NP-Hard.	David Maxwell Chickering, Christopher Meek, David Heckerman
2002	UAI	CFW: A Collaborative Filtering System Using Posteriors over Weights of Evidence.	Carl Myers Kadie, Christopher Meek, David Heckerman
2002	UAI	Staged Mixture Modelling and Boosting.	Christopher Meek, Bo Thiesson, David Heckerman
2002	UAI	An MDP-based Recommender System.	Guy Shani, Ronen I. Brafman, David Heckerman
2002	SDM	Autoregressive Tree Models for Time-Series Analysis.	Christopher Meek, David Maxwell Chickering, David Heckerman
2001	AISTATS	Learning mixtures of smooth, nonuniform deformation models for probabilistic image matching.	Nebojsa Jojic, Patrice Y. Simard, Brendan J. Frey, David Heckerman
2001	AISTATS	The Learning Curve Method Applied to Clustering.	Christopher Meek, Bo Thiesson, David Heckerman
2001	ICCV	Separating Appearance from Deformation.	Nebojsa Jojic, Patrice Y. Simard, Brendan J. Frey, David Heckerman
2000	KDD	Visualization of navigation patterns on a Web site using model-based clustering.	Igor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White
2000	UAI	A Decision Theoretic Approach to Targeted Advertising.	David Maxwell Chickering, David Heckerman
2000	UAI	Dependency Networks for Collaborative Filtering and Data Visualization.	David Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, Carl Myers Kadie
1999	AISTATS	On the geometry of DAG models with hidden variables.	Dan Geiger, David Heckerman, Henry King, Christopher Meek
1999	UAI	Fast Learning from Sparse Data.	David Maxwell Chickering, David Heckerman
1999	UAI	Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions.	Dan Geiger, David Heckerman
1998	UAI	Empirical Analysis of Predictive Algorithms for Collaborative Filtering.	John S. Breese, David Heckerman, Carl Myers Kadie
1998	UAI	Inferring Informational Goals from Free-Text Queries: A Bayesian Approach.	David Heckerman, Eric Horvitz
1998	UAI	The Lumire Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users.	Eric Horvitz, Jack S. Breese, David Heckerman, David Hovel, Koos Rommelse
1998	UAI	An Experimental Comparison of Several Clustering and Initialization Methods.	Marina Meila, David Heckerman
1998	UAI	Learning Mixtures of DAG Models.	Bo Thiesson, Christopher Meek, David Maxwell Chickering, David Heckerman
1997	AISTATS	A Comparison of Scientific and Engineering Criteria for Bayesian Model Selection.	David Heckerman, David Maxwell Chickering
1997	IJCAI	Challenge: What is the Impact of Bayesian Networks on Learning?	Nir Friedman, Moiss Goldszmidt, David Heckerman, Stuart Russell
1997	UAI	A Bayesian Approach to Learning Bayesian Networks with Local Structure.	David Maxwell Chickering, David Heckerman, Christopher Meek
1997	UAI	Models and Selection Criteria for Regression and Classification.	David Heckerman, Christopher Meek
1997	UAI	Structure and Parameter Learning for Causal Independence and Causal Interaction Models.	Christopher Meek, David Heckerman
1996	UAI	Decision-Theoretic Troubleshooting: A Framework for Repair and Experiment.	John S. Breese, David Heckerman
1996	UAI	Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network.	David Maxwell Chickering, David Heckerman
1996	UAI	Asymptotic Model Selection for Directed Networks with Hidden Variables.	Dan Geiger, David Heckerman, Christopher Meek
1995	ICML	Learning With Bayesian Networks (Abstract).	David Heckerman
1995	UAI	A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks.	Dan Geiger, David Heckerman
1995	UAI	A Bayesian Approach to Learning Causal Networks.	David Heckerman
1995	UAI	Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains.	David Heckerman, Dan Geiger
1995	UAI	A Definition and Graphical Representation for Causality.	David Heckerman, Ross D. Shachter
1994	KDD	Learning Bayesian Networks: The Combination of Knowledge and Statistical Data.	David Heckerman, Dan Geiger, David Maxwell Chickering
1994	UAI	Learning Gaussian Networks.	Dan Geiger, David Heckerman
1994	UAI	A New Look at Causal Independence.	David Heckerman, John S. Breese
1994	UAI	Learning Bayesian Networks: The Combination of Knowledge and Statistical Data.	David Heckerman, Dan Geiger, David Maxwell Chickering
1994	UAI	A Decision-based View of Causality.	David Heckerman, Ross D. Shachter
1993	UAI	Inference Algorithms for Similarity Networks.	Dan Geiger, David Heckerman
1993	UAI	Causal Independence for Knowledge Acquisition and Inference.	David Heckerman
1993	UAI	Diagnosis of Multiple Faults: A Sensitivity Analysis.	David Heckerman, Michael Shwe
1991	UAI	Advances in Probabilistic Reasoning.	Dan Geiger, David Heckerman
1991	UAI	An Approximate Nonmyopic Computation for Value of Information.	David Heckerman, Eric Horvitz, Blackford Middleton
1990	UAI	separable and transitive graphoids.	Dan Geiger, David Heckerman
1990	UAI	Similarity networks for the construction of multiple-faults belief networks.	David Heckerman
1990	UAI	Problem formulation as the reduction of a decision model.	David Heckerman, Eric Horvitz
1990	UAI	A combination of cutset conditioning with clique-tree propagation in the Pathfinder system.	Henri Jacques Suermondt, Gregory F. Cooper, David Heckerman
1989	IJCAI	Reflection and Action Under Scarce Resources: Theoretical Principles and Empirical Study.	Eric Horvitz, Gregory F. Cooper, David Heckerman
1989	UAI	A Tractable Inference Algorithm for Diagnosing Multiple Diseases.	David Heckerman
1988	UAI	An empirical comparison of three inference methods.	David Heckerman
1987	AAAI	On the Expressiveness of Rule-based Systems for Reasoning with Uncertainty.	David Heckerman, Eric Horvitz
1987	UAI	A Bayesian Perspective on Confidence.	David Heckerman, Holly Brgge Jimison
1986	AAAI	A Framework for Comparing Alternative Formalisms for Plausible Reasoning.	Eric Horvitz, David Heckerman, Curtis P. Langlotz
1986	UAI	An axiomatic framework for belief updates.	David Heckerman
1986	UAI	The myth of modularity in rule-based systems for reasoning with uncertainty.	David Heckerman, Eric Horvitz
1986	UAI	A backwards view for assessment.	Ross D. Shachter, David Heckerman
1985	UAI	Probabilistic Interpretation for MYCIN's Certainty Factors.	David Heckerman
1985	UAI	The Inconsistent Use of Measures of Certainty in Artificial Intelligence Research.	Eric Horvitz, David Heckerman