Waïss Azizian

Publications

Article dans une revue (3)

skwdro: a library for Wasserstein distributionally robust machine learning Florian Vincent,Waïss Azizian,Franck Iutzeler,Jérôme Malick Journal of Machine Learning Research, 2026, (Vol. 27), 27, pp.1-7 Article dans une revue hal-04919622v1
Almost sure convergence rates of stochastic gradient methods under gradient domination Simon Weissmann,Sara Klein,Waïss Azizian,Leif Döring Transactions of Machine Learning Research, 2025 Article dans une revue hal-05568073v1
Regularization for Wasserstein Distributionally Robust Optimization Waïss Azizian,Franck Iutzeler,Jérôme Malick ESAIM: Control, Optimisation and Calculus of Variations, 2023, 33, pp.31. ⟨10.1051/cocv/2023019⟩ Article dans une revue hal-03837681v2

Communication dans un congrès (6)

The global convergence of stochastic gradient descent in non-convex landscapes: Sharp estimates via large deviations Waïss Azizian,Franck Iutzeler,Jérôme Malick,Panayotis Mertikopoulos ICML 2025 - 42nd International Conference on Machine Learning, Jul 2025, Vancouver, Canada. pp.1-67 Communication dans un congrès hal-05136755v1
The Geometries of Truth Are Orthogonal Across Tasks Waïss Azizian,Michael Kirchhof,Eugene Ndiaye,Louis Bethune,Michal Kleinet al. ICML 2025 R2-FM Workshop, Jul 2025, Vancouver (BC), Canada Communication dans un congrès hal-05567983v1
What is the long-run distribution of stochastic gradient descent? A large deviations analysis Waïss Azizian,Franck Iutzeler,Jérôme Malick,Panayotis Mertikopoulos ICML 2024 - 41st International Conference on Machine Learning, Jul 2024, Vienna, Austria. pp.1-70 Communication dans un congrès hal-04629305v1
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models Waïss Azizian,Franck Iutzeler,Jérôme Malick 37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), Dec 2023, New Orleans, United States. pp.14584-14596, ⟨10.5555/3666122.3666763⟩ Communication dans un congrès hal-04106850v3
Expressive Power of Invariant and Equivariant Graph Neural Networks Waïss Azizian,Marc Lelarge ICLR 2021 - International Conference on Learning Representations, May 2021, Virtual, Unknown Region Communication dans un congrès hal-03464024v1
The last-iterate convergence rate of optimistic mirror descent in stochastic variational inequalities Waïss Azizian,Franck Iutzeler,Jérôme Malick,Panayotis Mertikopoulos COLT 2021 - 34th Annual Conference on Learning Theory, Aug 2021, Boulder, United States. pp.1-32, ⟨10.48550/arXiv.2107.01906⟩ Communication dans un congrès hal-03342583v1

Pré-publication, Document de travail (2)

How Does the Pretraining Distribution Shape In-Context Learning? Task Selection, Generalization, and Robustness Waïss Azizian,Ali Hasan 2025 Pré-publication, Document de travail hal-05568011v1
On the rate of convergence of Bregman proximal methods in constrained variational inequalities Waïss Azizian,Franck Iutzeler,Jérôme Malick,Panayotis Mertikopoulos 2022 Pré-publication, Document de travail hal-03873992v1