Towards Asymptotic Optimality with Conditioned Stochastic Gradient Descent. - Rémi Leluc; François Portier (CoRR, 2020)

Informative Clusters for Multivariate Extremes. - Hamid Jalalzai; Rémi Leluc (CoRR, 2020)

Feature Clustering for Support Identification in Extreme Regions. - Hamid Jalalzai; Rémi Leluc (ICML, 2021)

Control variate selection for Monte Carlo integration. - Rémi Leluc; François Portier; Johan Segers (Stat. Comput., 2021)

A Quadrature Rule combining Control Variates and Adaptive Importance Sampling. - Rémi Leluc; François Portier; Johan Segers; Aigerim Zhuman (NeurIPS, 2022)

Membership Inference Attacks via Adversarial Examples. - Hamid Jalalzai; Elie Kadoche; Rémi Leluc; Vincent Plassier (CoRR, 2022)

SGD with Coordinate Sampling: Theory and Practice. - Rémi Leluc; François Portier (J. Mach. Learn. Res., 2022)

Speeding up Monte Carlo Integration: Control Neighbors for Optimal Convergence. - Rémi Leluc; François Portier; Johan Segers; Aigerim Zhuman (CoRR, 2023)

MARLIM: Multi-Agent Reinforcement Learning for Inventory Management. - Rémi Leluc; Elie Kadoche; Antoine Bertoncello; Sébastien Gourvénec (CoRR, 2023)

Asymptotic Analysis of Conditioned Stochastic Gradient Descent. - Rémi Leluc; François Portier (Trans. Mach. Learn. Res., 2023)

Compression with Exact Error Distribution for Federated Learning. - Mahmoud Hegazy; Rémi Leluc; Cheuk Ting Li; Aymeric Dieuleveut (AISTATS, 2024)

Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates. - Rémi Leluc; Aymeric Dieuleveut; François Portier; Johan Segers; Aigerim Zhuman (ICML, 2024)