English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The developments of Rademacher complexity and PAC-Bayesian theory have beenlargely independent. One exception is the PAC-Bayes theorem of Kakade,Sridharan, and Tewari (2008), which is established via Rademacher complexitytheory by viewing Gibbs classifiers as linear operators. The goal of this paperis to extend this bridge between Rademacher complexity and state-of-the-artPAC-Bayesian theory. We first demonstrate that one can match the fast rate ofCatoni's PAC-Bayes bounds (Catoni, 2007) using shifted Rademacher processes(Wegkamp, 2003; Lecu\'{e} and Mitchell, 2012; Zhivotovskiy and Hanneke, 2018).We then derive a new fast-rate PAC-Bayes bound in terms of the "flatness" ofthe empirical risk surface on which the posterior concentrates. Our analysisestablishes a new framework for deriving fast-rate PAC-Bayes bounds and yieldsnew insights on PAC-Bayesian theory.

Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes