Mathieu Even

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 22

Top Topics

Statistical Learning

Stochastic Gradient Descent

Top Venues

Publications

Kevin Scaman, Mathieu Even, Batiste Le Bars, Laurent Massoulié
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles. AISTATS (2024)
Sayan Biswas, Mathieu Even, Anne-Marie Kermarrec, Laurent Massoulié, Rafael Pires, Rishi Sharma, Martijn de Vos
Beyond Noise: Privacy-Preserving Decentralized Learning with Virtual Nodes. CoRR (2024)
Mathieu Even, Luca Ganassali, Jakob Maier, Laurent Massoulié
Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem. CoRR (2024)
Mathieu Even, Anastasia Koloskova, Laurent Massoulié
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization. AISTATS (2024)
Mathieu Even
Stochastic Gradient Descent under Markovian Sampling Schemes. CoRR (2023)
Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion
(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability. CoRR (2023)
Kevin Scaman, Mathieu Even, Laurent Massoulié
Generalization Error of First-Order Methods for Statistical Learning with Generic Oracles. CoRR (2023)
Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion
(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability. NeurIPS (2023)
Mathieu Even, Anastasia Koloskova, Laurent Massoulié
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization. CoRR (2023)
Mathieu Even
Stochastic Gradient Descent under Markovian Sampling Schemes. ICML (2023)
Konstantin Mishchenko, Francis R. Bach, Mathieu Even, Blake E. Woodworth
Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays. CoRR (2022)
Konstantin Mishchenko, Francis R. Bach, Mathieu Even, Blake E. Woodworth
Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays. NeurIPS (2022)
Mathieu Even, Laurent Massoulié, Kevin Scaman
On Sample Optimality in Personalized Collaborative and Federated Learning. NeurIPS (2022)
Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging. NeurIPS (2022)
Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging. CoRR (2022)
Mathieu Even, Laurent Massoulié
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization. COLT (2021)
Mathieu Even, Hadrien Hendrikx, Laurent Massoulié
Decentralized Optimization with Heterogeneous Delays: a Continuous-Time Approach. CoRR (2021)
Radu-Alexandru Dragomir, Mathieu Even, Hadrien Hendrikx
Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction. ICML (2021)
Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Hadrien Hendrikx, Pierre Gaillard, Laurent Massoulié, Adrien B. Taylor
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms. NeurIPS (2021)
Mathieu Even, Laurent Massoulié
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization. CoRR (2021)
Mathieu Even, Raphaël Berthier, Francis R. Bach, Nicolas Flammarion, Pierre Gaillard, Hadrien Hendrikx, Laurent Massoulié, Adrien Taylor
A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip. CoRR (2021)
Mathieu Even, Hadrien Hendrikx, Laurent Massoulié
Asynchrony and Acceleration in Gossip Algorithms. CoRR (2020)