Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means.
CoRR, May, 2025
Differentially Private Policy Gradient.
CoRR, January, 2025
Differentially Private Model-Based Offline Reinforcement Learning.
CoRR, 2024
Measures of diversity and space-filling designs for categorical data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Stable Bounds on the Duality Gap of Separable Nonconvex Optimization Problems.
Math. Oper. Res., May, 2023
Clustered Multi-Agent Linear Bandits.
CoRR, 2023
Price of Safety in Linear Best Arm Identification.
CoRR, 2023
Multi-Agent Best Arm Identification with Private Communications.
Proceedings of the International Conference on Machine Learning, 2023
An α-No-Regret Algorithm For Graphical Bilinear Bandits.
CoRR, 2022
An $\alpha$-No-Regret Algorithm For Graphical Bilinear Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Deciphering Lasso-based Classification Through a Large Dimensional Analysis of the Iterative Soft-Thresholding Algorithm.
Proceedings of the International Conference on Machine Learning, 2022
Best Arm Identification in Graphical Bilinear Bandits.
Proceedings of the 38th International Conference on Machine Learning, 2021
Refined bounds for randomized experimental design.
CoRR, 2020
A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Parallel Contextual Bandits in Wireless Handover Optimization.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018
Adapting machine learning methods to U-statistics. (Adaptation des méthodes d'apprentissage aux U-statistiques).
PhD thesis, 2016
Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics.
J. Mach. Learn. Res., 2016
Decentralized Topic Modelling with Latent Dirichlet Allocation.
CoRR, 2016
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions.
Proceedings of the 33nd International Conference on Machine Learning, 2016
Extending Gossip Algorithms to Distributed Estimation of U-statistics.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015