Guedj, B;
(2019)
A Primer on PAC-Bayesian Learning.
In:
SMF 2018: Congrès de la Société Mathématique de France.
(pp. pp. 391-414).
Société Mathématique de France: Lille, France.
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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.
| Type: | Proceedings paper |
|---|---|
| Title: | A Primer on PAC-Bayesian Learning |
| Event: | the 2nd Congress of the French Mathematical Society (SMF) 2018 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://smf.emath.fr/node/144274 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | stat.ML, stat.ML, cs.LG |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10083910 |
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