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Cynthia Rudin - Publications

Affiliations: 
New York University, New York, NY, United States 
 Professor Duke University, Durham, NC 
Area:
Computation & Theory
Website:
http://www.cns.nyu.edu/~rudin/main.html
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18 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2019 Ban G, Rudin C. The Big Data Newsvendor: Practical Insights from Machine Learning Operations Research. 67: 90-108. DOI: 10.2139/Ssrn.2559116  0.311
2019 Rudin C. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead Nature Machine Intelligence. 1: 206-215. DOI: 10.1038/S42256-019-0048-X  0.346
2018 Rudin C, Ustun B. Optimized Scoring Systems: Toward Trust in Machine Learning for Healthcare and Criminal Justice Interfaces. 48: 449-466. DOI: 10.1287/Inte.2018.0957  0.336
2018 Rudin C, Ertekin Ş. Learning customized and optimized lists of rules with mathematical programming Mathematical Programming Computation. 10: 659-702. DOI: 10.1007/S12532-018-0143-8  0.333
2017 Zeng J, Ustun B, Rudin C. Interpretable classification models for recidivism prediction Journal of the Royal Statistical Society Series a-Statistics in Society. 180: 689-722. DOI: 10.1111/Rssa.12227  0.364
2016 Letham B, Letham PA, Rudin C, Browne EP. Prediction uncertainty and optimal experimental design for learning dynamical systems. Chaos (Woodbury, N.Y.). 26: 063110. PMID 27368775 DOI: 10.1063/1.4953795  0.333
2016 Souillard-Mandar W, Davis R, Rudin C, Au R, Libon DJ, Swenson R, Price CC, Lamar M, Penney DL. Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test. Machine Learning. 102: 393-441. PMID 27057085 DOI: 10.1007/S10994-015-5529-5  0.338
2015 Letham B, Rudin C, McCormick TH, Madigan D. Interpretable classifiers using rules and bayesian analysis: Building a better stroke prediction model Annals of Applied Statistics. 9: 1350-1371. DOI: 10.1214/15-Aoas848  0.344
2015 Ertekin Ş, Rudin C, McCormick TH. Reactive point processes: A new approach to predicting power failures in underground electrical systems Annals of Applied Statistics. 9: 122-144. DOI: 10.1214/14-AOAS789  0.306
2015 Ustun B, Rudin C. Supersparse linear integer models for optimized medical scoring systems Machine Learning. DOI: 10.1007/s10994-015-5528-6  0.31
2014 Tulabandhula T, Rudin C. On combining machine learning with decision making Machine Learning. 97: 33-64. DOI: 10.1007/s10994-014-5459-7  0.343
2014 Rudin C, Wagstaff KL. Machine learning for science and society Machine Learning. 95: 1-9. DOI: 10.1007/S10994-013-5425-9  0.34
2014 Kim B, Rudin C. Learning about meetings Data Mining and Knowledge Discovery. 28: 1134-1157. DOI: 10.1007/s10618-014-0348-z  0.302
2013 Rudin C, Letham B, Madigan D. Learning theory analysis for association rules and sequential event prediction Journal of Machine Learning Research. 14: 3441-3492. DOI: 10.7916/D82N50C1  0.353
2013 Letham B, Rudin C, Madigan D. Sequential event prediction Machine Learning. 93: 357-380. DOI: 10.1007/S10994-013-5356-5  0.305
2013 Letham B, Rudin C, Heller KA. Growing a list Data Mining and Knowledge Discovery. 27: 372-395. DOI: 10.1007/s10618-013-0329-7  0.31
2012 Rudin C, Waltz D, Anderson RN, Boulanger A, Salleb-Aouissi A, Chow M, Dutta H, Gross PN, Huang B, Ierome S, Isaac DF, Kressner A, Passonneau RJ, Radeva A, Wu L. Machine learning for the New York City power grid. Ieee Transactions On Pattern Analysis and Machine Intelligence. 34: 328-45. PMID 21576741 DOI: 10.1109/Tpami.2011.108  0.387
2010 Rudin C, Passonneau RJ, Radeva A, Dutta H, Ierome S, Isaac D. A process for predicting manhole events in Manhattan Machine Learning. 80: 1-31. DOI: 10.1007/S10994-009-5166-Y  0.333
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