Page, David

45 publications

CLeaR 2025 Temporal Inverse Probability Weighting for Causal Discovery in Controlled Before–After Studies: Discovering ADEs in Generics Aubrey Barnard, Peggy L. Peissig, David Page

MLHC 2024 MALADE: Orchestration of LLM-Powered Agents with Retrieval Augmented Generation for Pharmacovigilance Jihye Choi, Nils Palumbo, Prasad Chalasani, Matthew M. Engelhard, Somesh Jha, Anivarya Kumar, David Page

NeurIPS 2024 On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models Boyao Li, Alexander J. Thomson, Houssam Nassif, Matthew M. Engelhard, David Page

UAI 2023 Variable Importance Matching for Causal Inference Quinn Lanners, Harsh Parikh, Alexander Volfovsky, Cynthia Rudin, David Page

ICML 2020 CAUSE: Learning Granger Causality from Event Sequences Using Attribution Methods Wei Zhang, Thomas Panum, Somesh Jha, Prasad Chalasani, David Page

ICML 2019 AUCμ: A Performance Metric for Multi-Class Machine Learning Models Ross Kleiman, David Page

PGM 2018 Causal Structure Learning via Temporal Markov Networks Aubrey Barnard, David Page

UAI 2018 Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page

ICML 2018 Temporal Poisson Square Root Graphical Models Sinong Geng, Zhaobin Kuang, Peggy Peissig, David Page

NeurIPS 2017 A Screening Rule for L1-Regularized Ising Model Estimation Zhaobin Kuang, Sinong Geng, David Page

MLHC 2017 Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data Yujia Bao, Zhaobin Kuang, Peggy Peissig, David Page, Rebecca Willett

IJCAI 2016 Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page

JMLR 2016 Structure-Leveraged Methods in Breast Cancer Risk Prediction Jun Fan, Yirong Wu, Ming Yuan, David Page, Jie Liu, Irene M. Ong, Peggy Peissig, Elizabeth Burnside

AISTATS 2014 Learning Heterogeneous Hidden Markov Random Fields Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page

ICML 2014 Multiple Testing Under Dependence via Semiparametric Graphical Models Jie Liu, Chunming Zhang, Elizabeth Burnside, David Page

ECML-PKDD 2014 Support Vector Machines for Differential Prediction Finn Kuusisto, Vítor Santos Costa, Houssam Nassif, Elizabeth S. Burnside, David Page, Jude W. Shavlik

NeurIPS 2013 Bayesian Estimation of Latently-Grouped Parameters in Undirected Graphical Models Jie Liu, David Page

ECML-PKDD 2013 Forest-Based Point Process for Event Prediction from Electronic Health Records Jeremy C. Weiss, David Page

ECML-PKDD 2013 Score as You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, David Page, Jude W. Shavlik, Vítor Santos Costa

ICML 2012 Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events Jesse Davis, Vítor Santos Costa, Elizabeth Berg, David Page, Peggy L. Peissig, Michael Caldwell

UAI 2012 Graphical-Model Based Multiple Testing Under Dependence, with Applications to Genome-Wide Association Studies Jie Liu, Chunming Zhang, Catherine A. McCarty, Peggy L. Peissig, Elizabeth S. Burnside, David Page

AISTATS 2012 High-Dimensional Structured Feature Screening Using Binary Markov Random Fields Jie Liu, Chunming Zhang, Catherine Mccarty, Peggy Peissig, Elizabeth Burnside, David Page

AAAI 2012 Identifying Adverse Drug Events by Relational Learning David Page, Vítor Santos Costa, Sriraam Natarajan, Aubrey Barnard, Peggy L. Peissig, Michael Caldwell

NeurIPS 2012 Multiplicative Forests for Continuous-Time Processes Jeremy Weiss, Sriraam Natarajan, David Page

ECML-PKDD 2012 Relational Differential Prediction Houssam Nassif, Vítor Santos Costa, Elizabeth S. Burnside, David Page

ICML 2012 Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation Kendrick Boyd, Jesse Davis, David Page, Vítor Santos Costa

JMLR 2009 Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions Lisa Hellerstein, Bernard Rosell, Eric Bach, Soumya Ray, David Page

ICML 2007 An Integrated Approach to Feature Invention and Model Construction for Drug Activity Prediction Jesse Davis, Vítor Santos Costa, Soumya Ray, David Page

IJCAI 2007 Change of Representation for Statistical Relational Learning Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S. Burnside, David Page, Vítor Santos Costa

UAI 2007 Learning Bayesian Network Structure from Correlation-Immune Data Eric Lantz, Soumya Ray, David Page

MLJ 2006 Quantitative Pharmacophore Models with Inductive Logic Programming Ashwin Srinivasan, David Page, Rui Camacho, Ross D. King

ECML-PKDD 2005 An Integrated Approach to Learning Bayesian Networks of Rules Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Vítor Santos Costa

ICML 2005 Generalized Skewing for Functions with Continuous and Nominal Attributes Soumya Ray, David Page

ECML-PKDD 2005 Mode Directed Path Finding Irene M. Ong, Inês de Castro Dutra, David Page, Vítor Santos Costa

ICML 2005 Multi-Instance Tree Learning Hendrik Blockeel, David Page, Ashwin Srinivasan

IJCAI 2005 View Learning for Statistical Relational Learning: With an Application to Mammography Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Raghu Ramakrishnan, Vítor Santos Costa, Jude W. Shavlik

ICML 2005 Why Skewing Works: Learning Difficult Boolean Functions with Greedy Tree Learners Bernard Rosell, Lisa Hellerstein, Soumya Ray, David Page

ICML 2004 Sequential Skewing: An Improved Skewing Algorithm Soumya Ray, David Page

UAI 2003 CLP(BN): Constraint Logic Programming for Probabilistic Knowledge Vítor Santos Costa, David Page, Maleeha Qazi, James Cussens

JMLR 2003 ILP: A Short Look Back and a Longer Look Forward David Page, Ashwin Srinivasan

IJCAI 2003 Skewing: An Efficient Alternative to Lookahead for Decision Tree Induction David Page, Soumya Ray

ICML 2001 Multiple Instance Regression Soumya Ray, David Page

ICML 2000 Using Multiple Levels of Learning and Diverse Evidence to Uncover Coordinately Controlled Genes Mark W. Craven, David Page, Jude W. Shavlik, Joseph Bockhorst, Jeremy D. Glasner

MLJ 1998 Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL Paul W. Finn, Stephen H. Muggleton, David Page, Ashwin Srinivasan

MLJ 1997 Guest Editors' Introduction Stephen H. Muggleton, David Page