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Bibliographic Details
Main Authors: Tosh, Christopher, Hsu, Daniel
Format: Preprint
Published: 2021
Subjects:
Online Access:https://arxiv.org/abs/2112.12181
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Table of Contents:
  • Multi-group agnostic learning is a formal learning criterion that is concerned with the conditional risks of predictors within subgroups of a population. The criterion addresses recent practical concerns such as subgroup fairness and hidden stratification. This paper studies the structure of solutions to the multi-group learning problem, and provides simple and near-optimal algorithms for the learning problem.