Paul Viallard

According to our database, Paul Viallard authored at least 10 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

A general framework for the practical disintegration of PAC-Bayesian bounds.

Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant

Mach. Learn., February, 2024

Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures.

Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi

CoRR, 2024

A PAC-Bayesian Link Between Generalisation and Flat Minima.

Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj

CoRR, 2024

Tighter Generalisation Bounds via Interpolation.

Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj

CoRR, 2024

2023

From Mutual Information to Expected Dynamics: New Generalization Bounds for Heavy-Tailed SGD.

Benjamin Dupuis, Paul Viallard

CoRR, 2023

Learning via Wasserstein-Based High Probability Generalisation Bounds.

Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

A General Framework for the Derandomization of PAC-Bayesian Bounds.

Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant

CoRR, 2021

Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound.

Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound.

Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A PAC-Bayes Analysis of Adversarial Robustness.

Paul Viallard, Guillaume Vidot, Amaury Habrard, Emilie Morvant

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021