David Madigan - RankMe

67 papers A* 9A 11C 2Misc 1Journal 33Unranked 8

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Bayesian Posterior Interval Calibration to Improve the Interpretability of Observational Studies. Stat. Anal. Data Min. Jami J. Mulgrave, David Madigan, George Hripcsak
2021	J	`jnl`	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. Martijn J. Schuemie, Patrick B. Ryan, Nicole Pratt, Ruijun Chen, Seng Chan You, Harlan M. Krumholz, David Madigan, George Hripcsak, Marc A. Suchard
2020	—	`ed.`	FODS '20: ACM-IMS Foundations of Data Science Conference, Virtual Event, USA, October 19-20, 2020 FODS Jeannette M. Wing, David Madigan
2020	J	`jnl`	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. Martijn J. Schuemie, Patrick B. Ryan, Nicole Pratt, Ruijun Chen, Seng Chan You, Harlan M. Krumholz, David Madigan, George Hripcsak, Marc A. Suchard
2020	J	`jnl`	Principles of Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND). J. Am. Medical Informatics Assoc. Martijn J. Schuemie, Patrick B. Ryan, Nicole Pratt, Ruijun Chen, Seng Chan You, Harlan M. Krumholz, David Madigan, George Hripcsak, Marc A. Suchard
2020	J	`jnl`	Stable discovery of interpretable subgroups via calibration in causal studies. CoRR Raaz Dwivedi, Yan Shuo Tan, Briton Park, Mian Wei, Kevin Horgan, David Madigan, Bin Yu
2016	J	`jnl`	Hierarchical models for multiple, rare outcomes using massive observational healthcare databases. Stat. Anal. Data Min. Trevor R. Shaddox, Patrick B. Ryan, Martijn J. Schuemie, David Madigan, Marc A. Suchard
2016	J	`jnl`	The Factorized Self-Controlled Case Series Method: An Approach for Estimating the Effects of Many Drugs on Many Outcomes. J. Mach. Learn. Res. Ramin Moghaddass, Cynthia Rudin, David Madigan
2015	J	`jnl`	Birth month affects lifetime disease risk: a phenome-wide method. J. Am. Medical Informatics Assoc. Mary Regina Boland, Zach Shahn, David Madigan, George Hripcsak, Nicholas P. Tatonetti
2015	J	`jnl`	Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model. CoRR Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan
2015	—	`conf`	Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers. MedInfo 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
2015	J	`jnl`	Predicting health outcomes from high-dimensional longitudinal health histories using relational random forests. Stat. Anal. Data Min. Zach Shahn, Patrick B. Ryan, David Madigan
2014	J	`jnl`	Editorial. Stat. Anal. Data Min. David Madigan
2013	J	`jnl`	An Alternative Markov Property for Chain Graphs CoRR Steen A. Andersson, David Madigan, Michael D. Perlman
2013	—	`conf`	An Interpretable Stroke Prediction Model using Rules and Bayesian Analysis. AAAI (Late-Breaking Developments) Benjamin Letham, Cynthia Rudin, Tyler H. McCormick, David Madigan
2013	J	`jnl`	Learning theory analysis for association rules and sequential event prediction. J. Mach. Learn. Res. Cynthia Rudin, Benjamin Letham, David Madigan
2013	J	`jnl`	Massive Parallelization of Serial Inference Algorithms for a Complex Generalized Linear Model. ACM Trans. Model. Comput. Simul. Marc A. Suchard, Shawn E. Simpson, Ivan Zorych, Patrick B. Ryan, David Madigan
2013	J	`jnl`	Probabilistic Temporal Reasoning with Endogenous Change CoRR Steve Hanks, David Madigan, Jonathan Gavrin
2013	J	`jnl`	Sequential event prediction. Mach. Learn. Benjamin Letham, Cynthia Rudin, David Madigan
2011	A*	`conf`	Sequential Event Prediction with Association Rules. COLT Cynthia Rudin, Benjamin Letham, Ansaf Salleb-Aouissi, Eugene Kogan, David Madigan
2010	J	`jnl`	Large-scale regression-based pattern discovery: The example of screening the WHO global drug safety database. Stat. Anal. Data Min. Ola Caster, G. Niklas Norén, David Madigan, Andrew Bate
2009	J	`jnl`	Influence of the MedDRA Int. J. Medical Informatics Ronald K. Pearson, Manfred Hauben, David I. Goldsmith, A. Lawrence Gould, David Madigan, Donald J. O'Hara, Stephanie J. Reisinger, Alan Hochberg
2008	J	`jnl`	Algorithms for Sparse Linear Classifiers in the Massive Data Setting. J. Mach. Learn. Res. Suhrid Balakrishnan, David Madigan
2007	A*	`conf`	Finding Predictive Runs with LAPS. ICDM Suhrid Balakrishnan, David Madigan
2007	—	`ed.`	Intelligence and Security Informatics: Biosurveillance, Second NSF Workshop, BioSurveillance 2007, New Brunswick, NJ, USA, May 22, 2007, Proceedings. BioSurveillance Daniel Dajun Zeng, Ivan Gotham, Ken Komatsu, Cecil Lynch, Mark Thurmond, David Madigan, Bill Lober, James Kvach, Hsinchun Chen
2007	J	`jnl`	Large-Scale Bayesian Logistic Regression for Text Categorization. Technometrics Alexander Genkin, David D. Lewis, David Madigan
2007	C	`conf`	Sequential Decision Making Algorithms for Port of Entry Inspection: Overcoming Computational Challenges. ISI David Madigan, Sushil Mittal, Fred S. Roberts
2006	A*	`conf`	Constructing informative prior distributions from domain knowledge in text classification. SIGIR Aynur A. Dayanik, David D. Lewis, David Madigan, Vladimir Menkov, Alexander Genkin
2006	A*	`conf`	Decision Trees for Functional Variables. ICDM Suhrid Balakrishnan, David Madigan
2006	C	`conf`	Experimental Analysis of Sequential Decision Making Algorithms for Port of Entry Inspection Procedures. ISI Saket Anand, David Madigan, Richard J. Mammone, Saumitr Pathak, Fred S. Roberts
2006	J	`jnl`	Extreme value theory applied to document retrieval from large collections. Inf. Retr. David Madigan, Yehuda Vardi, Ishay Weissman
2005	A*	`conf`	Bayesian indoor positioning systems. INFOCOM David Madigan, E. Einahrawy, R. P. Martin, Wen-Hua Ju, Parameshwaran Krishnan, A. S. Krishnakumar
2005	—	`conf`	DIMACS at the TREC 2005 Genomics Track. TREC Aynur A. Dayanik, Alexander Genkin, Paul B. Kantor, David D. Lewis, David Madigan
2005	—	`ch.`	Probabilistic Temporal Reasoning. Handbook of Temporal Reasoning in Artificial Intelligence Steve Hanks, David Madigan
2004	—	`conf`	DIMACS at the TREC 2004 Genomics Track. TREC Aynur A. Dayanik, Dmitriy Fradkin, Alexander Genkin, Paul B. Kantor, David Madigan, David D. Lewis, Vladimir Menkov
2004	—	`conf`	Selected Data Mining Concepts. Discrete Methods in Epidemiology James Abello, Graham Cormode, Dmitriy Fradkin, David Madigan, Ofer Melnik, Ilya B. Muchnik
2003	J	`jnl`	A Sequential Monte Carlo Method for Bayesian Analysis of Massive Datasets. Data Min. Knowl. Discov. Greg Ridgeway, David Madigan
2003	A*	`conf`	Experiments with random projections for machine learning. KDD Dmitriy Fradkin, David Madigan
2003	J	`jnl`	Implementation Brief: A Two-way Messaging System to Enhance Antiretroviral Adherence. J. Am. Medical Informatics Assoc. Peter J. Dunbar, David Madigan, Lisa A. Grohskopf, Debra Revere, Jane Woodward, James Minstrell, Pamela A. Frick, Jane M. Simoni, Thomas M. Hooton
2003	A	`conf`	On Retrieval Properties of Samples of Large Collections. AISTATS David Madigan, Yehuda Vardi, Ishay Weissman
2003	A	`conf`	On the Naive Bayes Model for Text Categorization. AISTATS Susana Eyheramendy, David D. Lewis, David Madigan
2002	A*	`conf`	Bayesian analysis of massive datasets via particle filters. KDD Greg Ridgeway, David Madigan
2002	J	`jnl`	Likelihood-Based Data Squashing: A Modeling Approach to Instance Construction. Data Min. Knowl. Discov. David Madigan, Nandini Raghavan, William DuMouchel, Martha Nason, Christian Posse, Greg Ridgeway
2002	—	`conf`	Text forum features for small group discussions with facet-based pedagogy. CSCL Steven L. Tanimoto, Adam Carlson, Justin Husted, Earl B. Hunt, Josef Larsson, David Madigan, Jim Minstrell
2000	J	`jnl`	A Statistical, Nonparametric Methodology for Document Degradation Model Validation. IEEE Trans. Pattern Anal. Mach. Intell. Tapas Kanungo, Robert M. Haralick, Henry S. Baird, Werner Stuetzle, David Madigan
2000	J	`jnl`	KDD-99: The Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. SIGKDD Explor. Surajit Chaudhuri, David Madigan, Usama M. Fayyad
1999	A	`conf`	Bayesian graphical models, intention-to-treat, and the rubin causal Model. AISTATS David Madigan
1999	A	`conf`	Boosting methodology for regression problems. AISTATS Greg Ridgeway, David Madigan, Thomas Richardson
1999	J	`jnl`	Discussion on the paper by Friedman and Fisher. Stat. Comput. Greg Ridgeway, Thomas Richardson, David Madigan
1999	A*	`ed.`	Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego, CA, USA, August 15-18, 1999 KDD Usama M. Fayyad, Surajit Chaudhuri, David Madigan
1999	A	`conf`	Relaxing the local independence assumption for quantitative learning in acyclic directed graphical models through hierarchical partition models. AISTATS Daniela Golinelli, David Madigan, Guido Consonni
1998	A*	`conf`	Interpretable Boosted Naïve Bayes Classification. KDD Greg Ridgeway, David Madigan, Thomas Richardson, John O'Kane
1997	J	`jnl`	A Graphical Characterization of Lattice Conditional Independence Models. Ann. Math. Artif. Intell. Steen A. Andersson, David Madigan, Michael D. Perlman, Christopher M. Triggs
1997	A	`conf`	Bayesian Information Retrieval: Preliminary Evaluation. AISTATS Michelle Keim, David D. Lewis, David Madigan
1997	A	`conf`	Preface. AISTATS David Madigan, Padhraic Smyth
1997	A	`ed.`	Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, AISTATS 1997, Fort Lauderdale, Florida, USA, January, 4-7, 1997 AISTATS David Madigan, Padhraic Smyth
1997	J	`jnl`	Statistical Themes and Lessons for Data Mining. Data Min. Knowl. Discov. Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth
1996	A	`conf`	An Alternative Markov Property for Chain Graphs. UAI Steen A. Andersson, David Madigan, Michael D. Perlman
1996	—	`conf`	Benchmark Lessons and the World Wide Web: Tools for Teaching Statistics. ICLS Andrew Schaffner, Edith A. Graf, Earl Hunt, David Madigan, Jim Minstrell, Martha Nason
1996	J	`jnl`	Statistical Inference and Data Mining. Commun. ACM Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth
1995	J	`jnl`	Editorial: knowledge-based hypermedia. Int. J. Hum. Comput. Stud. David Madigan
1995	A	`conf`	On Test Selection Strategies for Belief Networks. AISTATS David Madigan, Russell G. Almond
1995	A	`conf`	Probabilistic Temporal Reasoning with Endogenous Change. UAI Steve Hanks, David Madigan, Jonathan Gavrin
1995	J	`jnl`	Repertory hypergrids for large-scale hypermedia linking. Int. J. Hum. Comput. Stud. David Madigan, C. Richard Chapman, Jonathan Gavrin, Ole Villumsen, John Boose
1994	Misc	`conf`	Document Degradation Models: Parameter Estimation and Model Validation. MVA Tapas Kanungo, Robert M. Haralick, Henry S. Baird, Werner Stuetzle, David Madigan
1994	J	`jnl`	Graphical models in applied multivariate statistics, by J. Whittaker, John Wiley & Sons, New York, 1990, 448 pp. Price: $59.95. Networks David Madigan
1994	—	`conf`	Repertory Hypergrids: An Application to Clinical Practice Guidelines. ECHT David Madigan, C. Richard Chapman, Jonathan Gavrin, Ole Villumsen, John Boose