Authors: | Tosh, C.; Hsu, D. |
Title: | Simple and near-optimal algorithms for hidden stratification and multi-group learning |
Conference Title: | 39th International Conference on Machine Learning (ICML) |
Abstract: | 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. |
Journal Title | Proceedings of Machine Learning Research |
Volume: | 162 |
Conference Dates: | 2022 Jul 17-23 |
Conference Location: | Baltimore, MD |
ISBN: | 2640-3498 |
Publisher: | Journal Machine Learning Research |
Date Published: | 2022-01-01 |
Start Page: | 21633 |
End Page: | 21657 |
Language: | English |
ACCESSION: | WOS:000900130202031 |
PROVIDER: | wos |
Notes: | Proceedings Paper -- Source: Wos |