Laurent Massoulié
22 papers · 2014–2025 · 6 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+8 more ↓ Show less ↑
🌍 Conference Polyglot (6) 🏃 Academic Marathon (11) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird
🌍
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
Research topics
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