pith. sign in

arxiv: 2605.30509 · v1 · pith:7B6PDGUFnew · submitted 2026-05-28 · 📊 stat.ML · cs.AI· cs.LG

Improved Distribution Estimation in ell_infty

classification 📊 stat.ML cs.AIcs.LG
keywords boundsdistributionempiricalimprovedinftybounddiscretedistributions
0
0 comments X
read the original abstract

We present improved bounds for estimating discrete probability distributions under the $\ell_\infty$ norm. These include minimax bounds in expectation and high-probability tail bounds. We resolve some of the open questions posed in Kontorovich and Painsky (JMLR, 2025) -- including a fully empirical version of the tightest risk bound they presented and identifying the form of the worst-case extremal distribution. Encouraging empirical results are reported as well.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.