Empirical Bernstein Inequality for Martingales : Application to Online Learning
type: Dataset
description: In this article we present a new empirical Bernstein inequality for bounded martingale difference sequences. This inequality refines the one by Freedman [1975] and is then used in order to bound the average risk of the hypotheses during an online learning process. We show theoretical and empirical evidences of the tightness of our result compared with the state of the art bound provided by Cesa-Bianchi and Gentile [2008].
issued: 2026-05-09T03:43:15.496092
language: en
modified: 2026-05-09T03:43:15.496096
contact point: Organization
  fn: CCSD
keyword: bernstein-inequality
keyword: empirical-inequality
keyword: infoeu-reposemanticspreprint
keyword: martingale
keyword: martingale-difference-sequence
keyword: online-learning
keyword: preprints-working-papers-
keyword: statmlstatistics-statmachine-learning-statml
landing page: https://hal.science/hal-00879909

Empirical Bernstein Inequality for Martingales : Application to Online Learning
type: Distribution
format: HTML
issued: 2026-05-09T03:43:15.506056
modified: 2026-05-09T03:43:15.485347
access URL: https://hal.science/hal-00879909

test_moissonnage_selune
type: Agent