Quentin Berthet

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 37

Top Topics

Efficient Optimization

Statistical Estimation

Satisfiability Problem

Top Venues

Publications

Tianlin Liu, Shangmin Guo, Leonardo Bianco, Daniele Calandriello, Quentin Berthet, Felipe Llinares, Jessica Hoffmann, Lucas Dixon, Michal Valko, Mathieu Blondel
Decoding-time Realignment of Language Models. CoRR (2024)
Pierre Marion, Anna Korba, Peter Bartlett, Mathieu Blondel, Valentin De Bortoli, Arnaud Doucet, Felipe Llinares-López, Courtney Paquette, Quentin Berthet
Implicit Diffusion: Efficient Optimization through Stochastic Sampling. CoRR (2024)
Lawrence Stewart, Francis R. Bach, Quentin Berthet, Jean-Philippe Vert
Regression as Classification: Influence of Task Formulation on Neural Network Features. AISTATS (2023)
Marin Ballu, Quentin Berthet
Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes. ICML (2023)
Lawrence Stewart, Francis R. Bach, Felipe Llinares-López, Quentin Berthet
Differentiable Clustering with Perturbed Spanning Forests. NeurIPS (2023)
Lawrence Stewart, Francis R. Bach, Felipe Llinares-López, Quentin Berthet
Differentiable Clustering with Perturbed Spanning Forests. CoRR (2023)
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert
Efficient and Modular Implicit Differentiation. NeurIPS (2022)
Lawrence Stewart, Francis R. Bach, Quentin Berthet, Jean-Philippe Vert
Regression as Classification: Influence of Task Formulation on Neural Network Features. CoRR (2022)
Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien B. Taylor
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. NeurIPS (2022)
Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien B. Taylor
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. CoRR (2022)
Artem R. Muliukov, Laurent Rodriguez, Benoît Miramond, Lyes Khacef, Joachim Schmidt, Quentin Berthet, Andres Upegui
A unified software/hardware scalable architecture for brain-inspired computing based on self-organizing neural models. CoRR (2022)
Marin Ballu, Quentin Berthet
Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes. CoRR (2022)
Andrew N. Carr, Quentin Berthet, Mathieu Blondel, Olivier Teboul, Neil Zeghidour
Self-Supervised Learning of Audio Representations from Permutations with Differentiable Ranking. CoRR (2021)
Quentin Berthet, Andres Upegui, Laurent Gantel, Alexandre Duc, Giulia Traverso
Post-Quantum Signature Coprocessor. IPDPS Workshops (2021)
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert
Efficient and Modular Implicit Differentiation. CoRR (2021)
Andrew N. Carr, Quentin Berthet, Mathieu Blondel, Olivier Teboul, Neil Zeghidour
Self-Supervised Learning of Audio Representations From Permutations With Differentiable Ranking. IEEE Signal Process. Lett. 28 (2021)
Marin Ballu, Quentin Berthet, Francis R. Bach
Stochastic Optimization for Regularized Wasserstein Estimators. ICML (2020)
Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga
Fast Differentiable Sorting and Ranking. CoRR (2020)
Marin Ballu, Quentin Berthet, Francis R. Bach
Stochastic Optimization for Regularized Wasserstein Estimators. CoRR (2020)
Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga
Fast Differentiable Sorting and Ranking. ICML (2020)
Quentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, Francis R. Bach
Learning with Differentiable Perturbed Optimizers. CoRR (2020)
Quentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, Francis R. Bach
Learning with Differentiable Pertubed Optimizers. NeurIPS (2020)
Quentin Berthet, Nicolai Baldin
Statistical and Computational Rates in Graph Logistic Regression. AISTATS (2020)
Quentin Berthet, Jordan S. Ellenberg
Detection of Planted Solutions for Flat Satisfiability Problems. AISTATS (2019)
Jonathan Weed, Quentin Berthet
Estimation of smooth densities in Wasserstein distance. COLT (2019)
Edouard Grave, Armand Joulin, Quentin Berthet
Unsupervised Alignment of Embeddings with Wasserstein Procrustes. AISTATS (2019)
Quentin Berthet, Varun Kanade
Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain. AISTATS (2019)
Xavier Fontaine, Quentin Berthet, Vianney Perchet
Regularized Contextual Bandits. AISTATS (2019)
Xavier Fontaine, Quentin Berthet, Vianney Perchet
Regularized Contextual Bandits. CoRR (2018)
Edouard Grave, Armand Joulin, Quentin Berthet
Unsupervised Alignment of Embeddings with Wasserstein Procrustes. CoRR (2018)
Quentin Berthet, Varun Kanade
Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain. CoRR (2018)
Quentin Berthet, Vianney Perchet
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe. NIPS (2017)
Quentin Berthet, Vianney Perchet
Bandit Optimization with Upper-Confidence Frank-Wolfe. CoRR (2017)
Quentin Berthet, Venkat Chandrasekaran
Resource Allocation for Statistical Estimation. Proc. IEEE 104 (1) (2016)
Tengyao Wang, Quentin Berthet, Yaniv Plan
Average-case Hardness of RIP Certification. CoRR (2016)
Tengyao Wang, Quentin Berthet, Yaniv Plan
Average-case hardness of RIP certification. NIPS (2016)
Quentin Berthet, Philippe Rigollet, Piyush Srivastava
Exact recovery in the Ising blockmodel. CoRR (2016)
Quentin Berthet, Jordan S. Ellenberg
Detection of Planted Solutions for Flat Satisfiability Problems. CoRR (2015)
Quentin Berthet
Optimal Testing for Planted Satisfiability Problems. CoRR (2014)
Quentin Berthet, Philippe Rigollet
Computational Lower Bounds for Sparse PCA CoRR (2013)
Quentin Berthet, Philippe Rigollet
Complexity Theoretic Lower Bounds for Sparse Principal Component Detection. COLT (2013)