Speaker |
Benjamin Guedj |
|---|---|
Affiliation |
UCL - INRIA |
Date |
Friday, 28 June 2019 |
Time |
13:00-14:00 |
Location |
Zoom |
Link |
Gatsby Computational Neuroscience Unit Ground Floor |
Event series |
Jump Trading/ELLIS CSML Seminar Series |
Abstract |
PAC-Bayes is a generic and flexible framework to address generalisation abilities of machine learning algorithms. It leverages the power of Bayesian inference and allows to derive new learning strategies. Benjamin will briefly present the key concepts of PAC-Bayes and illustrate how it can be used to study generalization properties of deep neural networks. Joint work with Gaël Letarte, Pascal Germain, François Laviolette (https://arxiv.org/abs/1905.13367) and John Shawe-Taylor (see our ICML 2019 tutorial https://bguedj.github.io/icml2019/index.html) |
Biography |