Learning bounded subsets of $L_p$
Machine Learning
2020-02-05 v1 Machine Learning
Statistics Theory
Statistics Theory
Abstract
We study learning problems in which the underlying class is a bounded subset of and the target belongs to . Previously, minimax sample complexity estimates were known under such boundedness assumptions only when . We present a sharp sample complexity estimate that holds for any . It is based on a learning procedure that is suited for heavy-tailed problems.
Cite
@article{arxiv.2002.01182,
title = {Learning bounded subsets of $L_p$},
author = {Shahar Mendelson},
journal= {arXiv preprint arXiv:2002.01182},
year = {2020}
}