David Madigan

According to our database, David Madigan authored at least 58 papers between 1994 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2021

Erratum to: Large-Scale Evidence Generation and Evaluation across a Network of Databases (LEGEND): Assessing Validity Using Hypertension as a Case Study.

Martijn J. Schuemie, Patrick B. Ryan, Nicole Pratt, Ruijun Chen, Seng Chan You, Harlan M. Krumholz, David Madigan, George Hripcsak, Marc A. Suchard

J. Am. Medical Informatics Assoc., 2021

2020

Principles of Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND).

Martijn J. Schuemie, Patrick B. Ryan, Nicole Pratt, Ruijun Chen, Seng Chan You, Harlan M. Krumholz, David Madigan, George Hripcsak, Marc A. Suchard

J. Am. Medical Informatics Assoc., 2020

Large-scale evidence generation and evaluation across a network of databases (LEGEND): assessing validity using hypertension as a case study.

Martijn J. Schuemie, Patrick B. Ryan, Nicole Pratt, Ruijun Chen, Seng Chan You, Harlan M. Krumholz, David Madigan, George Hripcsak, Marc A. Suchard

J. Am. Medical Informatics Assoc., 2020

Stable discovery of interpretable subgroups via calibration in causal studies.

Raaz Dwivedi, Yan Shuo Tan, Briton Park, Mian Wei, Kevin Horgan, David Madigan, Bin Yu

CoRR, 2020

2016

Hierarchical models for multiple, rare outcomes using massive observational healthcare databases.

Trevor R. Shaddox, Patrick B. Ryan, Martijn J. Schuemie, David Madigan, Marc A. Suchard

Stat. Anal. Data Min., 2016

The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes.

Ramin Moghaddass, Cynthia Rudin, David Madigan

J. Mach. Learn. Res., 2016

2015

Predicting health outcomes from high-dimensional longitudinal health histories using relational random forests.

Zach Shahn, Patrick B. Ryan, David Madigan

Stat. Anal. Data Min., 2015

Birth month affects lifetime disease risk: a phenome-wide method.

Mary Regina Boland, Zach Shahn, David Madigan, George Hripcsak, Nicholas P. Tatonetti

J. Am. Medical Informatics Assoc., 2015

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model.

Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan

CoRR, 2015

Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers.

George Hripcsak, Jon D. Duke, Nigam H. Shah, Christian G. Reich, Vojtech Huser, Martijn J. Schuemie, Marc A. Suchard, Rae Woong Park, Ian Chi Kei Wong, Peter R. Rijnbeek, Johan van der Lei, Nicole Pratt, G. Niklas Norén, Yu-Chuan Li, Paul E. Stang, David Madigan, Patrick B. Ryan

Proceedings of the MEDINFO 2015: eHealth-enabled Health, 2015

2014

Editorial.

David Madigan

Stat. Anal. Data Min., 2014

2013

Massive Parallelization of Serial Inference Algorithms for a Complex Generalized Linear Model.

Marc A. Suchard, Shawn E. Simpson, Ivan Zorych, Patrick B. Ryan, David Madigan

ACM Trans. Model. Comput. Simul., 2013

Sequential event prediction.

Benjamin Letham, Cynthia Rudin, David Madigan

Mach. Learn., 2013

Learning theory analysis for association rules and sequential event prediction.

Cynthia Rudin, Benjamin Letham, David Madigan

J. Mach. Learn. Res., 2013

An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis.

Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan

Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013

2011

Sequential Event Prediction with Association Rules.

Cynthia Rudin, Benjamin Letham, Ansaf Salleb-Aouissi, Eugene Kogan, David Madigan

Proceedings of the COLT 2011, 2011

2010

Large-scale regression-based pattern discovery: The example of screening the WHO global drug safety database.

Ola Caster, G. Niklas Norén, David Madigan, Andrew Bate

Stat. Anal. Data Min., 2010

2009

Influence of the MedDRA^® hierarchy on pharmacovigilance data mining results.

Ronald K. Pearson, Manfred Hauben, David I. Goldsmith, A. Lawrence Gould, David Madigan, Donald J. O'Hara, Stephanie J. Reisinger, Alan Hochberg

Int. J. Medical Informatics, 2009

2008

Algorithms for Sparse Linear Classifiers in the Massive Data Setting.

Suhrid Balakrishnan, David Madigan

J. Mach. Learn. Res., 2008

2007

Large-Scale Bayesian Logistic Regression for Text Categorization.

Alexander Genkin, David D. Lewis, David Madigan

Technometrics, 2007

Sequential Decision Making Algorithms for Port of Entry Inspection: Overcoming Computational Challenges.

David Madigan, Sushil Mittal, Fred S. Roberts

Proceedings of the IEEE International Conference on Intelligence and Security Informatics, 2007

Finding Predictive Runs with LAPS.

Suhrid Balakrishnan, David Madigan

Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

2006

Extreme value theory applied to document retrieval from large collections.

David Madigan, Yehuda Vardi, Ishay Weissman

Inf. Retr., 2006

Constructing informative prior distributions from domain knowledge in text classification.

Aynur A. Dayanik, David D. Lewis, David Madigan, Vladimir Menkov, Alexander Genkin

Proceedings of the SIGIR 2006: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2006

Experimental Analysis of Sequential Decision Making Algorithms for Port of Entry Inspection Procedures.

Saket Anand, David Madigan, Richard J. Mammone, Saumitr Pathak, Fred S. Roberts

Proceedings of the Intelligence and Security Informatics, 2006

Decision Trees for Functional Variables.

Suhrid Balakrishnan, David Madigan

Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

2005

Probabilistic Temporal Reasoning.

Steve Hanks, David Madigan

Proceedings of the Handbook of Temporal Reasoning in Artificial Intelligence, 2005

DIMACS at the TREC 2005 Genomics Track.

Aynur A. Dayanik, Alexander Genkin, Paul B. Kantor, David D. Lewis, David Madigan

Proceedings of the Fourteenth Text REtrieval Conference, 2005

Bayesian indoor positioning systems.

David Madigan, E. Einahrawy, R. P. Martin, Wen-Hua Ju, Parameshwaran Krishnan, A. S. Krishnakumar

Proceedings of the INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies, 2005

2004

DIMACS at the TREC 2004 Genomics Track.

Aynur A. Dayanik, Dmitriy Fradkin, Alexander Genkin, Paul B. Kantor, David Madigan, David D. Lewis, Vladimir Menkov

Proceedings of the Thirteenth Text REtrieval Conference, 2004

Selected Data Mining Concepts.

James Abello, Graham Cormode, Dmitriy Fradkin, David Madigan, Ofer Melnik, Ilya B. Muchnik

Proceedings of the Discrete Methods in Epidemiology, 2004

2003

Implementation Brief: A Two-way Messaging System to Enhance Antiretroviral Adherence.

Peter J. Dunbar, David Madigan, Lisa A. Grohskopf, Debra Revere, Jane Woodward, James Minstrell, Pamela A. Frick, Jane M. Simoni, Thomas M. Hooton

J. Am. Medical Informatics Assoc., 2003

A Sequential Monte Carlo Method for Bayesian Analysis of Massive Datasets.

Greg Ridgeway, David Madigan

Data Min. Knowl. Discov., 2003

Experiments with random projections for machine learning.

Dmitriy Fradkin, David Madigan

Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

On Retrieval Properties of Samples of Large Collections.

David Madigan, Yehuda Vardi, Ishay Weissman

Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

On the Naive Bayes Model for Text Categorization.

Susana Eyheramendy, David D. Lewis, David Madigan

Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

2002

Likelihood-Based Data Squashing: A Modeling Approach to Instance Construction.

David Madigan, Nandini Raghavan, William DuMouchel, Martha Nason, Christian Posse, Greg Ridgeway

Data Min. Knowl. Discov., 2002

Bayesian analysis of massive datasets via particle filters.

Greg Ridgeway, David Madigan

Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002

Text forum features for small group discussions with facet-based pedagogy.

Steven L. Tanimoto, Adam Carlson, Justin Husted, Earl B. Hunt, Josef Larsson, David Madigan, Jim Minstrell

Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community, 2002

2000

KDD-99: The Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

Surajit Chaudhuri, David Madigan, Usama M. Fayyad

SIGKDD Explor., 2000

A Statistical, Nonparametric Methodology for Document Degradation Model Validation.

Tapas Kanungo, Robert M. Haralick, Henry S. Baird, Werner Stuetzle, David Madigan

IEEE Trans. Pattern Anal. Mach. Intell., 2000

1999

Discussion on the paper by Friedman and Fisher.

Greg Ridgeway, Thomas Richardson, David Madigan

Stat. Comput., 1999

Boosting methodology for regression problems.

Greg Ridgeway, David Madigan, Thomas Richardson

Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

Bayesian graphical models, intention-to-treat, and the rubin causal Model.

David Madigan

Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

Relaxing the local independence assumption for quantitative learning in acyclic directed graphical models through hierarchical partition models.

Daniela Golinelli, David Madigan, Guido Consonni

Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, 1999

1998

Interpretable Boosted Naïve Bayes Classification.

Greg Ridgeway, David Madigan, Thomas Richardson, John O'Kane

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

1997

Statistical Themes and Lessons for Data Mining.

Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth

Data Min. Knowl. Discov., 1997

A Graphical Characterization of Lattice Conditional Independence Models.

Steen A. Andersson, David Madigan, Michael D. Perlman, Christopher M. Triggs

Ann. Math. Artif. Intell., 1997

1996

Statistical Inference and Data Mining.

Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth

Commun. ACM, 1996

An Alternative Markov Property for Chain Graphs.

Steen A. Andersson, David Madigan, Michael D. Perlman

Proceedings of the UAI '96: Proceedings of the Twelfth Annual Conference on Uncertainty in Artificial Intelligence, 1996

Benchmark Lessons and the World Wide Web: Tools for Teaching Statistics.

Andrew Schaffner, Edith A. Graf, Earl Hunt, David Madigan, Jim Minstrell, Martha Nason

Proceedings of the Learning for the Real World: Proceedings of the Second International Conference on the Learning Sciences, 1996

1995

Repertory hypergrids for large-scale hypermedia linking.

David Madigan, C. Richard Chapman, Jonathan Gavrin, Ole Villumsen, John Boose

Int. J. Hum. Comput. Stud., 1995

Editorial: knowledge-based hypermedia.

David Madigan

Int. J. Hum. Comput. Stud., 1995

Probabilistic Temporal Reasoning with Endogenous Change.

Steve Hanks, David Madigan, Jonathan Gavrin

Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

On Test Selection Strategies for Belief Networks.

David Madigan, Russell G. Almond

Proceedings of the Learning from Data, 1995

1994

Graphical models in applied multivariate statistics, by J. Whittaker, John Wiley & Sons, New York, 1990, 448 pp. Price: $59.95.

David Madigan

Networks, 1994

Document Degradation Models: Parameter Estimation and Model Validation.

Tapas Kanungo, Robert M. Haralick, Henry S. Baird, Werner Stuetzle, David Madigan

Proceedings of IAPR Workshop on Machine Vision Applications, 1994

Repertory Hypergrids: An Application to Clinical Practice Guidelines.

David Madigan, C. Richard Chapman, Jonathan Gavrin, Ole Villumsen, John Boose

Proceedings of the ECHT '94: European Conference on Hypertext Technology, 1994