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
- 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.