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A Primer on PAC-Bayesian Learning

Benjamin Guedj 1, 2, 3, 4, 5
1 MODAL - MOdel for Data Analysis and Learning
LPP - Laboratoire Paul Painlevé - UMR 8524, Université de Lille, Sciences et Technologies, Inria Lille - Nord Europe, METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694, Polytech Lille - École polytechnique universitaire de Lille
Abstract : Generalised Bayesian learning algorithms are increasingly popular in machine learning, due to their PAC generalisation properties and flexibility. The present paper aims at providing a self-contained survey on the resulting PAC-Bayes framework and some of its main theoretical and algorithmic developments.
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https://hal.inria.fr/hal-01983732
Contributor : Benjamin Guedj <>
Submitted on : Tuesday, May 7, 2019 - 11:15:35 PM
Last modification on : Tuesday, February 2, 2021 - 3:31:17 AM

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Benjamin Guedj. A Primer on PAC-Bayesian Learning. 2019. ⟨hal-01983732v3⟩

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