Publications

2025

• M. Haddouche, P. Viallard, U. Simsekli, B.Guedj, A PAC-Bayesian Link Between Generalisation and Flat Minima

2024

• M. Haddouche, B. Guedj, J. Shawe-Taylor Generalisation bounds for kernel PCA through PAC‐Bayes learning, Stat.
• M. Haddouche PAC-Bayes Learning From an Optimisation Perspective, PhD Thesis

2023

• P. Viallard, M.Haddouche, U. Simsekli, B.Guedj, Learning via Wasserstein-Based High Probability Generalisation Bounds, Neurips 2023
• M. Haddouche, B. Guedj, PAC-Bayes Generalisation Bounds for Heavy-Tailed Losses through Supermartingales, Transactions on Machine Learning Research.

2022

• M. Haddouche, B. Guedj, Online PAC-Bayes Learning, Neurips 2022

2021

• M. Haddouche, B. Guedj, O. Rivasplata and J. Shawe-Taylor. PAC-Bayes Unleashed: Generalisation Bounds with Unbounded Losses. Published at MDPI,Entropy, 2021.

Preprints

• M. Haddouche, O. Sakhi Logarithmic Smoothing for Adaptive PAC-Bayesian Off-Policy Learning
• A. Capitaine, M. Haddouche, E. Moulines, M. I. Jordan, E. Boursier, A. Durmus Online decision-Focused Learning
• B. Dupuis, D. Shariatian, M.Haddouche, A. Durmus, U. Simsekli, Algorithm-and Data-Dependent Generalization Bounds for Score-Based Generative Models
• B. Dupuis, M.Haddouche, G. Deligiannidis, U. Simsekli, Understanding the Generalization Error of Markov algorithms through Poissonization
• P. Viallard, M. Haddouche, U. Simsekli, B. Guedj, Tighter Generalisation Bounds via Interpolation
• P.Jobic, M.Haddouche, B. Guedj, Federated Learning with Nonvacuous Generalisation Bounds
• M. Haddouche, B. Guedj, Wasserstein PAC-Bayes Learning: Exploiting Optimisation Guarantees to Explain Generalisation.
• M. Haddouche, O. Wintenberger, B. Guedj Optimistically Tempered Online Learning.