Learning Laplacian Matrix from Bandlimited Graph Signals. - Batiste Le Bars; Pierre Humbert; Laurent Oudre; Argyris Kalogeratos (ICASSP, 2019)

A Probabilistic Framework to Node-level Anomaly Detection in Communication Networks. - Batiste Le Bars; Argyris Kalogeratos (INFOCOM, 2019)

Detecting multiple change-points in the time-varying Ising model. - Batiste Le Bars; Pierre Humbert; Argyris Kalogeratos; Nicolas Vayatis (CoRR, 2019)

Learning the piece-wise constant graph structure of a varying Ising model. - Batiste Le Bars; Pierre Humbert; Argyris Kalogeratos; Nicolas Vayatis (ICML, 2020)

Learning Laplacian Matrix from Graph Signals with Sparse Spectral Representation. - Pierre Humbert; Batiste Le Bars; Laurent Oudre; Argyris Kalogeratos; Nicolas Vayatis (J. Mach. Learn. Res., 2021)

Robust Kernel Density Estimation with Median-of-Means principle. - Pierre Humbert; Batiste Le Bars; Ludovic Minvielle (ICML, 2022)

Yes, Topology Matters in Decentralized Optimization: Refined Convergence and Topology Learning under Heterogeneous Data. - Batiste Le Bars; Aurélien Bellet; Marc Tommasi; Anne-Marie Kermarrec (CoRR, 2022)

Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data. - Batiste Le Bars; Aurélien Bellet; Marc Tommasi; Erick Lavoie; Anne-Marie Kermarrec (AISTATS, 2023)

One-Shot Federated Conformal Prediction. - Pierre Humbert; Batiste Le Bars; Aurélien Bellet; Sylvain Arlot (ICML, 2023)

Improved Stability and Generalization Analysis of the Decentralized SGD Algorithm. - Batiste Le Bars; Aurélien Bellet; Marc Tommasi (CoRR, 2023)

Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles. - Kevin Scaman; Mathieu Even; Batiste Le Bars; Laurent Massoulié (AISTATS, 2024)

Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm. - Batiste Le Bars; Aurélien Bellet; Marc Tommasi; Kevin Scaman; Giovanni Neglia (ICML, 2024)

On Volume Minimization in Conformal Regression. - Batiste Le Bars; Pierre Humbert (CoRR, 2025)

TAMIS: Tailored Membership Inference Attacks on Synthetic Data. - Paul Andrey; Batiste Le Bars; Marc Tommasi (CoRR, 2025)

Generalization under Byzantine & Poisoning Attacks: Tight Stability Bounds in Robust Distributed Learning. - Thomas Boudou; Batiste Le Bars; Nirupam Gupta; Aurélien Bellet (CoRR, 2025)

Adaptive collaboration for online personalized distributed learning with heterogeneous clients. - Constantin Philippenko; Batiste Le Bars; Kevin Scaman; Laurent Massoulié (CoRR, 2025)