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A condensed primer on PAC-Bayesian learning

发布时间:2020-12-14 作者: 浏览次数:
Speaker: Benjamin Guedj DateTime: 2020年12月17日(周四)下午16:30-17:30
Brief Introduction to Speaker:

Benjamin Guedj is a principal research fellow in Machine learning at University College London (centre for Artificial intelligence, department of Computer Science) and a tenured research scientist at Inria. He is also a visiting researcher at The Alan Turing Institute, fellow of the Royal Statistical Society and member of the ELLIS Society.

Place: 腾讯会议(会议号请联系左国新老师索取)
Abstract:Generalised Bayesian learning algorithms are increasingly popular in machine learning, due to their PAC generalisation properties and flexibility. This talk aims at providing a self-contained survey on the resulting PAC-Bayes framework and some of its main theoretical and algorithmic developments.