Paper of the Month

Once a month during the academic year our faculty will select a paper which we encourage our students to read and discuss. Papers featured in this section should be generally understood by graduate students, and will be selected either because of their impact, or historical value, or because they contain useful (perhaps overlooked) techniques or results.

Paper of the Month: September 2022

Belkin, M., Hsu, D., Ma, S., & Mandal, S. (2019). Reconciling modern machine-learning practice and the classical bias–variance trade-off. Proceedings of the National Academy of Sciences, 116(32), 15849-15854.

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Paper of the Month: April 2022

Liu, Y., & Xie, J. (2020). Cauchy Combination Test: A Powerful Test With Analytic p-Value Calculation Under Arbitrary Dependency Structures Journal of the American Statistical Association, 115(529), 393-402.

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