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A Meta-Analysis of Overfitting in Machine Learning

Rebecca Roelofs, Vaishaal Shankar, Benjamin Recht, Sara Fridovich-Keil, Moritz Hardt, John Miller, Ludwig Schmidt

Neural Information Processing Systems

In each competition, numerous practitioners repeatedly evaluated their progress against a holdout set that forms the basis of a public ranking availablethroughout the competition. Performance on a separate test set used only oncedetermined the final ranking.


730ce0ae730f39e4d77b0f04a8afe4be-Supplemental-Conference.pdf

Neural Information Processing Systems

This paper studies the use of a machine learning-based estimator as a control variate for mitigating the variance of Monte Carlo sampling. Specifically, we seek to uncover the key factors that influence the efficiency of control variates in reducing variance.



fa93d7bfb48450e1af63c8fa647d317f-Paper-Conference.pdf

Neural Information Processing Systems

Tothebestofourknowledge, ourenhanced latent space blind model, optimization scheme, NFAEandFM2A havenot been reported in the previous literature.