116 citations · 151 across the 6 of their papers we have counts for
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stat.AP2018
Using permutations to assess confounding in machine learning applications for digital health
Elias Chaibub Neto, Abhishek Pratap, Thanneer M Perumal +4
Clinical machine learning applications are often plagued with confounders that can impact the generalizability and predictive performance of the learners. Confounding is especially…
stat.AP2018
Using permutations to detect, quantify and correct for confounding in machine learning predictions
Elias Chaibub Neto
Clinical machine learning applications are often plagued with confounders that are clinically irrelevant, but can still artificially boost the predictive performance of the algorit…
stat.ML2018
Detecting Learning vs Memorization in Deep Neural Networks using Shared Structure Validation Sets
Elias Chaibub Neto
The roles played by learning and memorization represent an important topic in deep learning research. Recent work on this subject has shown that the optimization behavior of DNNs t…