PAC-Bayes Mini-tutorial: A Continuous Union Bound
Machine Learning
2014-05-08 v1
Abstract
When I first encountered PAC-Bayesian concentration inequalities they seemed to me to be rather disconnected from good old-fashioned results like Hoeffding's and Bernstein's inequalities. But, at least for one flavour of the PAC-Bayesian bounds, there is actually a very close relation, and the main innovation is a continuous version of the union bound, along with some ingenious applications. Here's the gist of what's going on, presented from a machine learning perspective.
Cite
@article{arxiv.1405.1580,
title = {PAC-Bayes Mini-tutorial: A Continuous Union Bound},
author = {Tim van Erven},
journal= {arXiv preprint arXiv:1405.1580},
year = {2014}
}