Massoulie, Laurent

25 publications

NeurIPS 2025 Graph Alignment via Birkhoff Relaxation Sushil Mahavir Varma, Irène Waldspurger, Laurent Massoulié

AAAI 2025 In-Depth Analysis of Low-Rank Matrix Factorisation in a Federated Setting Constantin Philippenko, Kevin Scaman, Laurent Massoulié

NeurIPS 2024 Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem Mathieu Even, Luca Ganassali, Jakob Maier, Laurent Massoulié

AISTATS 2024 Asynchronous SGD on Graphs: A Unified Framework for Asynchronous Decentralized and Federated Optimization Mathieu Even, Anastasia Koloskova, Laurent Massoulie

NeurIPS 2024 Barely Random Algorithms and Collective Metrical Task Systems Romain Cosson, Laurent Massoulié

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

NeurIPSW 2022 Asynchronous Speedup in Decentralized Optimization Mathieu Even, Hadrien Hendrikx, Laurent Massoulié

NeurIPS 2022 Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié

NeurIPS 2022 On Sample Optimality in Personalized Collaborative and Federated Learning Mathieu Even, Laurent Massoulié, Kevin Scaman

COLT 2021 Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization Mathieu Even, Laurent Massoulie

NeurIPS 2021 Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Hadrien Hendrikx, Pierre Gaillard, Laurent Massoulié, Adrien Taylor

COLT 2021 Impossibility of Partial Recovery in the Graph Alignment Problem Luca Ganassali, Laurent Massoulie, Marc Lelarge

NeurIPS 2020 Dual-Free Stochastic Decentralized Optimization with Variance Reduction Hadrien Hendrikx, Francis R. Bach, Laurent Massoulié

COLT 2020 From Tree Matching to Sparse Graph Alignment Luca Ganassali, Laurent Massoulié

ICML 2020 Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization Hadrien Hendrikx, Lin Xiao, Sebastien Bubeck, Francis Bach, Laurent Massoulie

AISTATS 2019 Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives Hadrien Hendrikx, Francis Bach, Laurent Massoulie

NeurIPS 2019 An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums Hadrien Hendrikx, Francis Bach, Laurent Massoulié

JMLR 2019 Optimal Convergence Rates for Convex Distributed Optimization in Networks Kevin Scaman, Francis Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié

COLT 2019 Planting Trees in Graphs, and Finding Them Back Laurent Massoulié, Ludovic Stephan, Don Towsley

COLT 2019 Robustness of Spectral Methods for Community Detection Ludovic Stephan, Laurent Massoulié

NeurIPS 2018 Optimal Algorithms for Non-Smooth Distributed Optimization in Networks Kevin Scaman, Francis Bach, Sebastien Bubeck, Laurent Massoulié, Yin Tat Lee

ICML 2017 Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks Kevin Scaman, Francis Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié

COLT 2016 On the Capacity of Information Processing Systems Laurent Massoulié, Kuang Xu

COLT 2014 Edge Label Inference in Generalized Stochastic Block Models: From Spectral Theory to Impossibility Results Jiaming Xu, Laurent Massoulié, Marc Lelarge

ICML 2012 Comparison-Based Learning with Rank Nets Amin Karbasi, Stratis Ioannidis, Laurent Massoulié