Mathieu Even
12 papers · 2021–2025 · 5 conferences · across top CS/AI conferences
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Conference Polyglot
(5)
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(5)
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(12)
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(5)
Conferences
NIPS (6)
AISTATS (2)
ICML (2)
COLT (1)
ICLR (1)
Top co-authors
Research topics
Keywords
stochastic gradient descent
(4)
convex optimization
(2)
asynchronous stochastic gradient descent
(2)
decentralized optimization
(2)
distributed optimization
(2)
federated learning
(2)
variance reduction
(2)
non-convex optimization
(1)
distributed learning
(1)
differential privacy
(1)
sample complexity
(1)
point cloud
(1)
optimal transport
(1)
stochastic gradient
(1)
sparse regression
(1)
procrustes analysis
(1)
empirical risk minimization
(1)
generalization error
(1)
asynchronous computation
(1)
transfer learning
(1)
Papers
Long-Context Linear System Identification
ICLR 2025
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
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization
AISTATS 2024
Stochastic Gradient Descent under Markovian Sampling Schemes
ICML 2023
(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
NIPS 2023
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging
NIPS 2022
Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays
NIPS 2022
On Sample Optimality in Personalized Collaborative and Federated Learning
NIPS 2022
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization
COLT 2021
Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction
ICML 2021
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms
NIPS 2021