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Mathieu Blondel

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Learning with Fitzpatrick Losses

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May 23, 2024
Seta Rakotomandimby, Jean-Philippe Chancelier, Michel de Lara, Mathieu Blondel

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The Elements of Differentiable Programming

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Mar 21, 2024
Mathieu Blondel, Vincent Roulet

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Implicit Diffusion: Efficient Optimization through Stochastic Sampling

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Feb 08, 2024
Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet

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How do Transformers perform In-Context Autoregressive Learning?

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Feb 08, 2024
Michael E. Sander, Raja Giryes, Taiji Suzuki, Mathieu Blondel, Gabriel Peyré

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Direct Language Model Alignment from Online AI Feedback

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Feb 07, 2024
Shangmin Guo, Biao Zhang, Tianlin Liu, Tianqi Liu, Misha Khalman, Felipe Llinares, Alexandre Rame, Thomas Mesnard, Yao Zhao, Bilal Piot, Johan Ferret, Mathieu Blondel

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Decoding-time Realignment of Language Models

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Feb 05, 2024
Tianlin Liu, Shangmin Guo, Leonardo Bianco, Daniele Calandriello, Quentin Berthet, Felipe Llinares, Jessica Hoffmann, Lucas Dixon, Michal Valko, Mathieu Blondel

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Routers in Vision Mixture of Experts: An Empirical Study

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Jan 29, 2024
Tianlin Liu, Mathieu Blondel, Carlos Riquelme, Joan Puigcerver

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Dual Gauss-Newton Directions for Deep Learning

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Aug 17, 2023
Vincent Roulet, Mathieu Blondel

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Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective

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Feb 06, 2023
Michael E. Sander, Joan Puigcerver, Josip Djolonga, Gabriel Peyré, Mathieu Blondel

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Sparsity-Constrained Optimal Transport

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Sep 30, 2022
Tianlin Liu, Joan Puigcerver, Mathieu Blondel

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