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Big Data|July 22, 2016
Finding Patterns with a Rotten Core: Data Mining for Crime Series with CoresTong Wang, Cynthia Rudin, Daniel Wagner, et al.Nature Machine Intelligence|May 23, 2022
Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models InsteadCynthia RudinBig Data|July 22, 2016
Tire Changes, Fresh Air, and Yellow Flags: Challenges in Predictive Analytics for Professional RacingTheja Tulabandhula, Cynthia RudinProceedings of the National Academy of Sciences of the United States of America|October 2, 2023
Interpretable algorithmic forensicsBrandon L Garrett, Cynthia RudinJournal of Machine Learning Research : JMLR|August 2, 2021
All Models are Wrong, but <i>Many</i> are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models SimultaneouslyAaron Fisher, Cynthia Rudin, Francesca DominiciPlos One|March 25, 2016
A Computational Model of Inhibition of HIV-1 by Interferon-AlphaEdward P Browne, Benjamin Letham, Cynthia RudinJournal of Machine Learning Research : JMLR|November 7, 2024
Rethinking Nonlinear Instrumental Variable Models through Prediction ValidityChunxiao Li, Cynthia Rudin, Tyler H McCormickProceedings of Machine Learning Research|September 24, 2024
Optimal Sparse Survival TreesRui Zhang, Rui Xin, Margo Seltzer, et al.Advances in Neural Information Processing Systems|March 20, 2024
OKRidge: Scalable Optimal k-Sparse Ridge RegressionJiachang Liu, Sam Rosen, Chudi Zhong, et al.Pageof 371