Cooper, Gregory F.

41 publications

PGM 2024 Learning Causal Markov Boundaries with Mixed Observational and Experimental Data Konstantina Lelova, Gregory F. Cooper, Sofia Triantafillou

AISTATS 2023 Learning Treatment Effects from Observational and Experimental Data Sofia Triantafillou, Fattaneh Jabbari, Gregory F. Cooper

UAI 2021 Causal and Interventional Markov Boundaries Sofia Triantafillou, Fattaneh Jabbari, Gregory F. Cooper

AAAI 2021 Learning Adjustment Sets from Observational and Limited Experimental Data Sofia Triantafillou, Gregory F. Cooper

AISTATS 2020 On the Completeness of Causal Discovery in the Presence of Latent Confounding with Tiered Background Knowledge Bryan Andrews, Peter Spirtes, Gregory F. Cooper

PGM 2018 Instance-Specific Bayesian Network Structure Learning Fattaneh Jabbari, Shyam Visweswaran, Gregory F. Cooper

ECML-PKDD 2017 Discovery of Causal Models That Contain Latent Variables Through Bayesian Scoring of Independence Constraints Fattaneh Jabbari, Joseph D. Ramsey, Peter Spirtes, Gregory F. Cooper

AAAI 2015 Obtaining Well Calibrated Probabilities Using Bayesian Binning Mahdi Pakdaman Naeini, Gregory F. Cooper, Milos Hauskrecht

ECML-PKDD 2012 A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules Iyad Batal, Gregory F. Cooper, Milos Hauskrecht

MLJ 2010 A Multivariate Bayesian Scan Statistic for Early Event Detection and Characterization Daniel B. Neill, Gregory F. Cooper

JMLR 2010 Learning Instance-Specific Predictive Models Shyam Visweswaran, Gregory F. Cooper

UAI 2006 A Theoretical Study of Y Structures for Causal Discovery Subramani Mani, Gregory F. Cooper, Peter Spirtes

NeurIPS 2005 A Bayesian Spatial Scan Statistic Daniel B. Neill, Andrew W. Moore, Gregory F. Cooper

UAI 2004 Bayesian Biosurveillance of Disease Outbreaks Gregory F. Cooper, Denver Dash, John D. Levander, Weng-Keen Wong, William R. Hogan, Michael M. Wagner

NeurIPS 2004 Instance-Specific Bayesian Model Averaging for Classification Shyam Visweswaran, Gregory F. Cooper

JMLR 2004 Model Averaging for Prediction with Discrete Bayesian Networks Denver Dash, Gregory F. Cooper

ICML 2003 Bayesian Network Anomaly Pattern Detection for Disease Outbreaks Weng-Keen Wong, Andrew W. Moore, Gregory F. Cooper, Michael M. Wagner

AISTATS 2003 Model Averaging with Bayesian Network Classifiers Denver Dash, Gregory F. Cooper

UAI 2002 A Bayesian Network Scoring Metic That Is Based on Globally Uniform Parameter Priors Mehmet Kayaalp, Gregory F. Cooper

ICML 2002 Exact Model Averaging with Naive Bayesian Classifiers Denver Dash, Gregory F. Cooper

AAAI 2002 Rule-Based Anomaly Pattern Detection for Detecting Disease Outbreaks Weng-Keen Wong, Andrew W. Moore, Gregory F. Cooper, Michael M. Wagner

AISTATS 2001 A Simulation Study of Three Related Causal Data Mining Algorithms Subramani Mani, Gregory F. Cooper

AISTATS 2001 Piecewise Linear Instrumental Variable Estimation of Causal Influence Richard Scheines, Gregory F. Cooper, Changwon Yoo, Tianjiao Chu

AISTATS 2001 Predicting with Variables Constructed from Temporal Sequences Mehmet Kayaalp, Gregory F. Cooper, Gilles Clermont

UAI 2000 A Bayesian Method for Causal Modeling and Discovery Under Selection Gregory F. Cooper

UAI 1999 A Bayesian Network Classifier That Combines a Finite Mixture Model and a NaIve Bayes Model Stefano Monti, Gregory F. Cooper

AISTATS 1999 An Experiment in Causal Discovery Using a Pneumonia Database Peter Spirtes, Gregory F. Cooper

AAAI 1999 Causal Discovery from Population-Based Infant Birth and Death Records Subramani Mani, Gregory F. Cooper

UAI 1999 Causal Discovery from a Mixture of Experimental and Observational Data Gregory F. Cooper, Changwon Yoo

UAI 1998 A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data Stefano Monti, Gregory F. Cooper

UAI 1998 UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, University of Wisconsin Business School, Madison, Wisconsin, USA, July 24-26, 1998 Gregory F. Cooper, Serafín Moral

UAI 1996 A Structurally and Temporally Extended Bayesian Belief Network Model: Definitions, Properties, and Modeling Techniques Constantin F. Aliferis, Gregory F. Cooper

NeurIPS 1996 Learning Bayesian Belief Networks with Neural Network Estimators Stefano Monti, Gregory F. Cooper

AISTATS 1995 Causal Discovery from Data in the Presence of Selection Bias Gregory F. Cooper

UAI 1994 An Evaluation of an Algorithm for Inductive Learning of Bayesian Belief Networks Using Simulated Data Sets Constantin F. Aliferis, Gregory F. Cooper

MLJ 1992 A Bayesian Method for the Induction of Probabilistic Networks from Data Gregory F. Cooper, Edward Herskovits

UAI 1990 A Combination of Cutset Conditioning with Clique-Tree Propagation in the Pathfinder System Henri Jacques Suermondt, Gregory F. Cooper, David Heckerman

UAI 1990 An Entropy-Driven System for Construction of Probabilistic Expert Systems from Databases Edward Herskovits, Gregory F. Cooper

IJCAI 1989 Reflection and Action Under Scarce Resources: Theoretical Principles and Empirical Study Eric Horvitz, Gregory F. Cooper, David Heckerman

UAI 1987 An Algorithm for Computing Probabilistic Propositions Gregory F. Cooper

UAI 1987 Bayesian Belief Network Inference Using Simulation Homer L. Chin, Gregory F. Cooper