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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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Submitted on : Tuesday, May 7, 2019 - 11:15:35 PM
Last modification on : Wednesday, March 23, 2022 - 3:51:06 PM


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  • HAL Id : hal-01983732, version 3


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



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