Publications

Christian Lebeda, Mathieu Even, Aurélien Bellet, Julie Josse (2025). Model Agnostic Differentially Private Causal Inference.

Mathieu Even, Julie Josse (2025). Rethinking the Win Ratio A Causal Framework for Hierarchical Outcome Analysis.

Oğuz Kaan Yüksel, Mathieu Even, Nicolas Flammarion (2024). Long-Context Linear System Identification.

Mathieu Even, Hadrien Hendrikx, Laurent Massoulié (2024). Asynchronous speedup in decentralized optimization. IEEE Transactions on Automatic Control.

Mathieu Even, Anastasia Koloskova, Laurent Massoulié (2024). Asynchronous SGD on Graphs - a Unified Framework for Asynchronous Decentralized and Federated Optimization. AISTATS, 2024.

Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion (2023). Implicit Regularisation, Large Stepsizes and Edge of Stability for (S)GD over Diagonal Linear Networks. Neural Information Processing Systems (NeurIPS), 2023.

Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion (2023). Aligning Embeddings and Geometric Random Graphs, Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem. Neural Information Processing Systems (NeurIPS), 2023.

Mathieu Even (2023). Stochastic Gradient Descent under Markov Chain Sampling Schemes. International conference on Machine Learning, 2023.

Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié (2022). Muffliato Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging. Neural Information Processing Systems (NeurIPS), 2022.

Konstantin Mischenko, Francis Bach, Mathieu Even, Blake Woodworth (2022). Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays. Neural Information Processing Systems (NeurIPS), 2022.

Mathieu Even, Laurent Massoulié, Kevin Scaman (2022). On Sample Optimality in Personalized Federated and Collaborative Learning. Neural Information Processing Systems (NeurIPS), 2022.

Mathieu Even, Raphaël Berthier, Francis Bach, Nicolas Flamarrion, Pierre Gaillard, Hadrien Hendrikx, Laurent Massoulié, Adrien Taylor (2021). A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip. NeurIPS2021 Outstanding Paper Award.

Mathieu Even, Hadrien Hendrikx, Laurent Massoulié (2021). Decentralized Optimization with Heterogeneous Delays: a Continuous-Time Approach.

RA Dragomir, Mathieu Even, Hadrien Hendrikx (2021). Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction. ICML2021.

Mathieu Even, Laurent Massoulié (2021). Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization. COLT2021.