← Authors

Laurent Massoulié

22 papers · 2014–2025 · 6 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (5) 🌈 Renaissance Researcher (6) 🗺️ Taxonomy Completionist (37) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🏃 Academic Marathon (11) 🧭 Keyword Pioneer 🗃️ Keyword Collector (103) 📈 Trend Setter 💎 Century Club (22) 🔥 Unstoppable (7) ⚡ Prolific Year (5)

Conferences

NIPS (8) COLT (7) AISTATS (3) ICML (2) AAAI (1) JMLR (1)

Top co-authors

Mathieu Even (7) Francis Bach (6) Kevin Scaman (6) Hadrien Hendrikx (5) Sébastien Bubeck (4) Luca Ganassali (3) Yin Tat Lee (3) Ludovic Stephan (2) Francis R. Bach (2) marc lelarge (2)

Research topics

Differential Privacy (1) Statistics (1)

Keywords

distributed optimization (6) decentralized optimization (6) convergence rate (4) gossip algorithm (3) convex optimization (3) distributed learning (3) network optimization (3) federated learning (3) graph alignment (3) stochastic gradient (2) community detection (2) random graph (2) stochastic block model (2) primal-dual algorithm (2) empirical risk minimization (2) nesterov acceleration (2) sample complexity (1) stochastic gradient descent (1) optimal transport (1) graph analysis (1)

Papers

In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting AAAI 2025
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization AISTATS 2024
Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem NIPS 2024
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles AISTATS 2024
Barely Random Algorithms and Collective Metrical Task Systems NIPS 2024
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging NIPS 2022
On Sample Optimality in Personalized Collaborative and Federated Learning NIPS 2022
Impossibility of Partial Recovery in the Graph Alignment Problem COLT 2021
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms NIPS 2021
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization COLT 2021
Dual-Free Stochastic Decentralized Optimization with Variance Reduction NIPS 2020
From tree matching to sparse graph alignment COLT 2020
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization ICML 2020
Optimal Convergence Rates for Convex Distributed Optimization in Networks JMLR 2019
An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums NIPS 2019
Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives AISTATS 2019
Planting trees in graphs, and finding them back COLT 2019
Robustness of Spectral Methods for Community Detection COLT 2019
Optimal Algorithms for Non-Smooth Distributed Optimization in Networks NIPS 2018
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks ICML 2017
On the capacity of information processing systems COLT 2016
Edge Label Inference in Generalized Stochastic Block Models: from Spectral Theory to Impossibility Results COLT 2014