Bertrand, Quentin

15 publications

NeurIPS 2025 On the Closed-Form of Flow Matching: Generalization Does Not Arise from Target Stochasticity Quentin Bertrand, Anne Gagneux, Mathurin Massias, Rémi Emonet

ICML 2025 Self-Play $q$-Learners Can Provably Collude in the Iterated Prisoner’s Dilemma Quentin Bertrand, Juan Agustin Duque, Emilio Calvano, Gauthier Gidel

MLOSS 2025 Skglm: Improving Scikit-Learn for Regularized Generalized Linear Models Badr Moufad, Pierre-Antoine Bannier, Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias

ICLR 2024 On the Stability of Iterative Retraining of Generative Models on Their Own Data Quentin Bertrand, Joey Bose, Alexandre Duplessis, Marco Jiralerspong, Gauthier Gidel

NeurIPS 2024 Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences Damien Ferbach, Quentin Bertrand, Avishek Joey Bose, Gauthier Gidel

ICMLW 2023 Omega: Optimistic EMA Gradients Juan Ramirez, Rohan Sukumaran, Quentin Bertrand, Gauthier Gidel

AISTATS 2023 On the Limitations of the Elo, Real-World Games Are Transitive, Not Additive Quentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel

ICML 2023 Synergies Between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning Sebastien Lachapelle, Tristan Deleu, Divyat Mahajan, Ioannis Mitliagkas, Yoshua Bengio, Simon Lacoste-Julien, Quentin Bertrand

NeurIPS 2022 Beyond L1: Faster and Better Sparse Models with Skglm Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias

JMLR 2022 Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon

NeurIPS 2022 The Curse of Unrolling: Rate of Differentiating Through Optimization Damien Scieur, Gauthier Gidel, Quentin Bertrand, Fabian Pedregosa

AISTATS 2021 Anderson Acceleration of Coordinate Descent Quentin Bertrand, Mathurin Massias

ICML 2020 Implicit Differentiation of Lasso-Type Models for Hyperparameter Optimization Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel, Samuel Vaiter, Alexandre Gramfort, Joseph Salmon

AISTATS 2020 Support Recovery and Sup-Norm Convergence Rates for Sparse Pivotal Estimation Mathurin Massias, Quentin Bertrand, Alexandre Gramfort, Joseph Salmon

NeurIPS 2019 Handling Correlated and Repeated Measurements with the Smoothed Multivariate Square-Root Lasso Quentin Bertrand, Mathurin Massias, Alexandre Gramfort, Joseph Salmon