Part 2 Pac Bayesian Learning For Deep Learning

Media Summary: Talk by Pascal Germain at NIPS 2012 Workshop Multi-trade-off in Olivier Catoni - Dimension-free PAC-Bayesian Bounds (Talk) In this video, I give a short introduction into our current research paper "

Part 2 Pac Bayesian Learning For Deep Learning - Detailed Analysis & Overview

Talk by Pascal Germain at NIPS 2012 Workshop Multi-trade-off in Olivier Catoni - Dimension-free PAC-Bayesian Bounds (Talk) In this video, I give a short introduction into our current research paper " Next couple of lectures i will be talking about Benjamin Guedj (2021), A (condensed) primer on In this lecture we introduce a compression approach to obtain bounds for test-train risk difference. We prove a

Photo Gallery

Part 2: PAC bayesian learning for deep learning

PAC Bayesian Learning and Domain Adaptation

A (condensed) primer on PAC-Bayesian Learning

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

Theoretical Deep Learning #2: PAC-bayesian bounds. Part2

Olivier Catoni - Dimension-free PAC-Bayesian Bounds (Talk)

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

Eric J. Ma - An Attempt At Demystifying Bayesian Deep Learning

AISTATS 2023: PAC-Bayesian Learning of Optimization Algorithms

Part 1: generalization and PAC bayesian learning

First lecture on Bayesian Deep Learning and Uncertainty Quantification

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

View Detailed Profile

Part 2: PAC bayesian learning for deep learning

Part 2: PAC bayesian learning for deep learning

an application.

PAC Bayesian Learning and Domain Adaptation

PAC Bayesian Learning and Domain Adaptation

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

A (condensed) primer on PAC-Bayesian Learning

A (condensed) primer on PAC-Bayesian Learning

A (condensed) primer on

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

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

The goal of

Theoretical Deep Learning #2: PAC-bayesian bounds. Part2

Theoretical Deep Learning #2: PAC-bayesian bounds. Part2

In this lecture we prove several

Olivier Catoni - Dimension-free PAC-Bayesian Bounds (Talk)

Olivier Catoni - Dimension-free PAC-Bayesian Bounds (Talk)

Olivier Catoni - Dimension-free PAC-Bayesian Bounds (Talk)

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

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

A (condensed) primer on

Eric J. Ma - An Attempt At Demystifying Bayesian Deep Learning

Eric J. Ma - An Attempt At Demystifying Bayesian Deep Learning

PyData New York City 2017 Slides: https://ericmjl.github.io/

AISTATS 2023: PAC-Bayesian Learning of Optimization Algorithms

AISTATS 2023: PAC-Bayesian Learning of Optimization Algorithms

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

Part 1: generalization and PAC bayesian learning

Part 1: generalization and PAC bayesian learning

Next couple of lectures i will be talking about

First lecture on Bayesian Deep Learning and Uncertainty Quantification

First lecture on Bayesian Deep Learning and Uncertainty Quantification

First lecture on

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

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

Benjamin Guedj (2021), A (condensed) primer on

Theoretical Deep Learning #2: PAC-bayesian bounds. Part5

Theoretical Deep Learning #2: PAC-bayesian bounds. Part5

In this lecture we introduce a compression approach to obtain bounds for test-train risk difference. We prove a