Laurent Massoulié
23 papers · 2014–2026 · 6 venues · across top CS/AI venues
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🗺️ Taxonomy Completionist (38) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Gold 🐣 Hot Topic Early Bird
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Century Club · Bronze
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Prolific Year · Productive
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Research topics
Machine Learning
(20)
Mathematics & Optimization
(17)
Optimization & Theory
(17)
Optimization
(11)
Computer Science
(7)
Mathematics
(6)
Foundations
(5)
Artificial Intelligence
(4)
Core Methods
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Learning Types
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Core AI
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Learning Paradigms
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Computer Vision
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Data Science & Analytics
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Security & Privacy
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Keywords
decentralized optimization
(6)
distributed optimization
(6)
graph alignment
(4)
convergence rate
(4)
convex optimization
(3)
distributed learning
(3)
federated learning
(3)
network optimization
(3)
gossip algorithm
(3)
random graph
(3)
nesterov acceleration
(2)
stochastic gradient
(2)
stochastic block model
(2)
phase transition
(2)
community detection
(2)
primal-dual algorithm
(2)
empirical risk minimization
(2)
sample complexity
(1)
stochastic gradient descent
(1)
optimal transport
(1)
Papers
Phase Transition in Convex Relaxations for Graph Alignment
COLT 2026
In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting
AAAI 2025
Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem
NeurIPS 2024
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization
AISTATS 2024
Barely Random Algorithms and Collective Metrical Task Systems
NeurIPS 2024
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles
AISTATS 2024
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging
NeurIPS 2022
On Sample Optimality in Personalized Collaborative and Federated Learning
NeurIPS 2022
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization
COLT 2021
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms
NeurIPS 2021
Impossibility of Partial Recovery in the Graph Alignment Problem
COLT 2021
Dual-Free Stochastic Decentralized Optimization with Variance Reduction
NeurIPS 2020
From tree matching to sparse graph alignment
COLT 2020
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization
ICML 2020
Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives
AISTATS 2019
An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums
NeurIPS 2019
Optimal Convergence Rates for Convex Distributed Optimization in Networks
JMLR 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
NeurIPS 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