Pac Bayes

The PAC-Bayes Guarantee

... is the

An Introduction to PAC-Bayes

Speakers: Andrew Foong, David Burt, Javier Antoran Abstract:

Pierre Alquier (ESSEC) - PAC Bayes: introduction and overview

Abstract: The

PAC-Bayesian Machine Learning: Learning by Optimizing a Performance Guarantee

The goal of machine learning algorithms is to produce predictors having the smallest possible risk (expected loss). Since the ...

A (condensed) primer on PAC-Bayesian learning, followed by News from the PAC-Bayes frontline

A (condensed) primer on

Part 1: generalization and PAC bayesian learning

So

Studying Generalization in Deep Learning via PAC-Bayes

Gintare Karolina Dziugaite (Element AI) https://simons.berkeley.edu/talks/tbd-77 Frontiers of Deep Learning.

NIPS 2016 spotlight - PAC Bayesian Theory Meets Bayesian Inference

NIPS 2016 spotlight Poster #29 (Mon Dec 5th) Manuscript: https://arxiv.org/abs/1605.08636 Slides: ...

PAC-Bayesian approaches to understanding generalization in deep learning - Gintare Dziugaite

Workshop on Theory of Deep Learning: Where next? Topic:

[ML/DL] PAC-Bayesian Bound for Deep Learning Models

In this video, we discuss the

PAC-Bayes control for obstacle avoidance

Results from: "

A (condensed) primer on PAC-Bayesian Learning

A (condensed) primer on

CS 159 (Spring 2021) -- PAC-Bayesian Theory

Slides: https://1five9.github.io/slides/learning/11.pdf.

Pascal Germain (Université Laval) - PAC-Bayes Hypernetworks

Abstract: The

PAC Bayesian Learning and Domain Adaptation

Talk by Pascal Germain at NIPS 2012 Workshop Multi-trade-off in Machine Learning.

AISTATS 2023: PAC-Bayesian Learning of Optimization Algorithms

In this video, I give a short introduction into our current research paper "

Yevgeny Seldin (University of Copenhagen) - Recursive PAC Bayes

Abstract:

CVPR2023: Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization

This is a video recording that introduces our recent CVPR paper that aims to improve the empirical robust accuracy of vision ...