David Madigan

Publication Activity (10 Years)

Years Active: 1994-2021
Publications (10 Years): 10

Top Topics

Hierarchical Models

Markov Property

Top Venues

J. Am. Medical Informatics Assoc.

Stat. Anal. Data Min.

J. Mach. Learn. Res.

Publications

Martijn J. Schuemie, Patrick B. Ryan, Nicole Pratt, Ruijun Chen, Seng Chan You, Harlan M. Krumholz, David Madigan, George Hripcsak, Marc A. Suchard
Erratum to: Large-Scale Evidence Generation and Evaluation across a Network of Databases (LEGEND): Assessing Validity Using Hypertension as a Case Study. J. Am. Medical Informatics Assoc. 28 (1) (2021)
Raaz Dwivedi, Yan Shuo Tan, Briton Park, Mian Wei, Kevin Horgan, David Madigan, Bin Yu
Stable discovery of interpretable subgroups via calibration in causal studies. CoRR (2020)
Martijn J. Schuemie, Patrick B. Ryan, Nicole Pratt, Ruijun Chen, Seng Chan You, Harlan M. Krumholz, David Madigan, George Hripcsak, Marc A. Suchard
Principles of Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND). J. Am. Medical Informatics Assoc. 27 (8) (2020)
Martijn J. Schuemie, Patrick B. Ryan, Nicole Pratt, Ruijun Chen, Seng Chan You, Harlan M. Krumholz, David Madigan, George Hripcsak, Marc A. Suchard
Large-scale evidence generation and evaluation across a network of databases (LEGEND): assessing validity using hypertension as a case study. J. Am. Medical Informatics Assoc. 27 (8) (2020)
Trevor R. Shaddox, Patrick B. Ryan, Martijn J. Schuemie, David Madigan, Marc A. Suchard
Hierarchical models for multiple, rare outcomes using massive observational healthcare databases. Stat. Anal. Data Min. 9 (4) (2016)
Ramin Moghaddass, Cynthia Rudin, David Madigan
The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes. J. Mach. Learn. Res. 17 (2016)
Mary Regina Boland, Zach Shahn, David Madigan, George Hripcsak, Nicholas P. Tatonetti
Birth month affects lifetime disease risk: a phenome-wide method. J. Am. Medical Informatics Assoc. 22 (5) (2015)
Zach Shahn, Patrick B. Ryan, David Madigan
Predicting health outcomes from high-dimensional longitudinal health histories using relational random forests. Stat. Anal. Data Min. 8 (2) (2015)
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
Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers. MedInfo (2015)
Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan
Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model. CoRR (2015)
David Madigan
Editorial. Stat. Anal. Data Min. 7 (6) (2014)
Marc A. Suchard, Shawn E. Simpson, Ivan Zorych, Patrick B. Ryan, David Madigan
Massive Parallelization of Serial Inference Algorithms for a Complex Generalized Linear Model. ACM Trans. Model. Comput. Simul. 23 (1) (2013)
Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan
An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis. AAAI (Late-Breaking Developments) (2013)
Cynthia Rudin, Benjamin Letham, David Madigan
Learning theory analysis for association rules and sequential event prediction. J. Mach. Learn. Res. 14 (1) (2013)
Steen A. Andersson, David Madigan, Michael D. Perlman
An Alternative Markov Property for Chain Graphs CoRR (2013)
Benjamin Letham, Cynthia Rudin, David Madigan
Sequential event prediction. Mach. Learn. 93 (2-3) (2013)
Steve Hanks, David Madigan, Jonathan Gavrin
Probabilistic Temporal Reasoning with Endogenous Change CoRR (2013)
Cynthia Rudin, Benjamin Letham, Ansaf Salleb-Aouissi, Eugene Kogan, David Madigan
Sequential Event Prediction with Association Rules. COLT (2011)
Ola Caster, G. Niklas Norén, David Madigan, Andrew Bate
Large-scale regression-based pattern discovery: The example of screening the WHO global drug safety database. Stat. Anal. Data Min. 3 (4) (2010)
Ronald K. Pearson, Manfred Hauben, David I. Goldsmith, A. Lawrence Gould, David Madigan, Donald J. O'Hara, Stephanie J. Reisinger, Alan Hochberg
hierarchy on pharmacovigilance data mining results. Int. J. Medical Informatics 78 (12) (2009)
Suhrid Balakrishnan, David Madigan
Algorithms for Sparse Linear Classifiers in the Massive Data Setting. J. Mach. Learn. Res. 9 (2008)
David Madigan, Sushil Mittal, Fred S. Roberts
Sequential Decision Making Algorithms for Port of Entry Inspection: Overcoming Computational Challenges. ISI (2007)
Suhrid Balakrishnan, David Madigan
Finding Predictive Runs with LAPS. ICDM (2007)
Alexander Genkin, David D. Lewis, David Madigan
Large-Scale Bayesian Logistic Regression for Text Categorization. Technometrics 49 (3) (2007)
Suhrid Balakrishnan, David Madigan
Decision Trees for Functional Variables. ICDM (2006)
David Madigan, Yehuda Vardi, Ishay Weissman
Extreme value theory applied to document retrieval from large collections. Inf. Retr. 9 (3) (2006)
Aynur A. Dayanik, David D. Lewis, David Madigan, Vladimir Menkov, Alexander Genkin
Constructing informative prior distributions from domain knowledge in text classification. SIGIR (2006)
Saket Anand, David Madigan, Richard J. Mammone, Saumitr Pathak, Fred S. Roberts
Experimental Analysis of Sequential Decision Making Algorithms for Port of Entry Inspection Procedures. ISI (2006)
Aynur A. Dayanik, Alexander Genkin, Paul B. Kantor, David D. Lewis, David Madigan
DIMACS at the TREC 2005 Genomics Track. TREC (2005)
David Madigan, E. Einahrawy, R. P. Martin, Wen-Hua Ju, Parameshwaran Krishnan, A. S. Krishnakumar
Bayesian indoor positioning systems. INFOCOM (2005)
Aynur A. Dayanik, Dmitriy Fradkin, Alexander Genkin, Paul B. Kantor, David Madigan, David D. Lewis, Vladimir Menkov
DIMACS at the TREC 2004 Genomics Track. TREC (2004)
James Abello, Graham Cormode, Dmitriy Fradkin, David Madigan, Ofer Melnik, Ilya B. Muchnik
Selected Data Mining Concepts. Discrete Methods in Epidemiology (2004)
Susana Eyheramendy, David D. Lewis, David Madigan
On the Naive Bayes Model for Text Categorization. AISTATS (2003)
Peter J. Dunbar, David Madigan, Lisa A. Grohskopf, Debra Revere, Jane Woodward, James Minstrell, Pamela A. Frick, Jane M. Simoni, Thomas M. Hooton
Implementation Brief: A Two-way Messaging System to Enhance Antiretroviral Adherence. J. Am. Medical Informatics Assoc. 10 (1) (2003)
Dmitriy Fradkin, David Madigan
Experiments with random projections for machine learning. KDD (2003)
Greg Ridgeway, David Madigan
A Sequential Monte Carlo Method for Bayesian Analysis of Massive Datasets. Data Min. Knowl. Discov. 7 (3) (2003)
David Madigan, Yehuda Vardi, Ishay Weissman
On Retrieval Properties of Samples of Large Collections. AISTATS (2003)
David Madigan, Nandini Raghavan, William DuMouchel, Martha Nason, Christian Posse, Greg Ridgeway
Likelihood-Based Data Squashing: A Modeling Approach to Instance Construction. Data Min. Knowl. Discov. 6 (2) (2002)
Steven L. Tanimoto, Adam Carlson, Justin Husted, Earl B. Hunt, Josef Larsson, David Madigan, Jim Minstrell
Text forum features for small group discussions with facet-based pedagogy. CSCL (2002)
Greg Ridgeway, David Madigan
Bayesian analysis of massive datasets via particle filters. KDD (2002)
Tapas Kanungo, Robert M. Haralick, Henry S. Baird, Werner Stuetzle, David Madigan
A Statistical, Nonparametric Methodology for Document Degradation Model Validation. IEEE Trans. Pattern Anal. Mach. Intell. 22 (11) (2000)
Surajit Chaudhuri, David Madigan, Usama M. Fayyad
KDD-99: The Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. SIGKDD Explor. 1 (2) (2000)
Daniela Golinelli, David Madigan, Guido Consonni
Relaxing the local independence assumption for quantitative learning in acyclic directed graphical models through hierarchical partition models. AISTATS (1999)
Greg Ridgeway, Thomas Richardson, David Madigan
Discussion on the paper by Friedman and Fisher. Stat. Comput. 9 (2) (1999)
Greg Ridgeway, David Madigan, Thomas Richardson
Boosting methodology for regression problems. AISTATS (1999)
David Madigan
Bayesian graphical models, intention-to-treat, and the rubin causal Model. AISTATS (1999)
Greg Ridgeway, David Madigan, Thomas Richardson, John O'Kane
Interpretable Boosted Naïve Bayes Classification. KDD (1998)
Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth
Statistical Themes and Lessons for Data Mining. Data Min. Knowl. Discov. 1 (1) (1997)
Steen A. Andersson, David Madigan, Michael D. Perlman, Christopher M. Triggs
A Graphical Characterization of Lattice Conditional Independence Models. Ann. Math. Artif. Intell. 21 (1) (1997)
Andrew Schaffner, Edith A. Graf, Earl Hunt, David Madigan, Jim Minstrell, Martha Nason
Benchmark Lessons and the World Wide Web: Tools for Teaching Statistics. ICLS (1996)
Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth
Statistical Inference and Data Mining. Commun. ACM 39 (11) (1996)
Steen A. Andersson, David Madigan, Michael D. Perlman
An Alternative Markov Property for Chain Graphs. UAI (1996)
David Madigan, C. Richard Chapman, Jonathan Gavrin, Ole Villumsen, John Boose
Repertory hypergrids for large-scale hypermedia linking. Int. J. Hum. Comput. Stud. 43 (3) (1995)
David Madigan, Russell G. Almond
On Test Selection Strategies for Belief Networks. AISTATS (1995)
David Madigan
Editorial: knowledge-based hypermedia. Int. J. Hum. Comput. Stud. 43 (3) (1995)
Steve Hanks, David Madigan, Jonathan Gavrin
Probabilistic Temporal Reasoning with Endogenous Change. UAI (1995)
David Madigan, C. Richard Chapman, Jonathan Gavrin, Ole Villumsen, John Boose
Repertory Hypergrids: An Application to Clinical Practice Guidelines. ECHT (1994)
Tapas Kanungo, Robert M. Haralick, Henry S. Baird, Werner Stuetzle, David Madigan
Document Degradation Models: Parameter Estimation and Model Validation. MVA (1994)
David Madigan
Graphical models in applied multivariate statistics, by J. Whittaker, John Wiley & Sons, New York, 1990, 448 pp. Price: $59.95. Networks 24 (2) (1994)