Complexity Theoretic Lower Bounds for Sparse Principal Component Detection. - Quentin Berthet; Philippe Rigollet (COLT, 2013)

Computational Lower Bounds for Sparse PCA - Quentin Berthet; Philippe Rigollet (CoRR, 2013)

Optimal Testing for Planted Satisfiability Problems. - Quentin Berthet (CoRR, 2014)

Statistical and Computational Tradeoffs in High-dimensional Problems - Quentin Berthet (2014)

Average-case hardness of RIP certification. - Tengyao Wang; Quentin Berthet; Yaniv Plan (NIPS, 2016)

Exact recovery in the Ising blockmodel. - Quentin Berthet; Philippe Rigollet; Piyush Srivastava 001 (CoRR, 2016)

Resource Allocation for Statistical Estimation. - Quentin Berthet; Venkat Chandrasekaran (Proc. IEEE, 2016)

Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe. - Quentin Berthet; Vianney Perchet (NIPS, 2017)

Bandit Optimization with Upper-Confidence Frank-Wolfe. - Quentin Berthet; Vianney Perchet (CoRR, 2017)

Detection of Planted Solutions for Flat Satisfiability Problems. - Quentin Berthet; Jordan S. Ellenberg (AISTATS, 2019)

Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain. - Quentin Berthet; Varun Kanade (AISTATS, 2019)

Regularized Contextual Bandits. - Xavier Fontaine; Quentin Berthet; Vianney Perchet (AISTATS, 2019)

Unsupervised Alignment of Embeddings with Wasserstein Procrustes. - Edouard Grave; Armand Joulin; Quentin Berthet (AISTATS, 2019)

Estimation of smooth densities in Wasserstein distance. - Jonathan Weed; Quentin Berthet (COLT, 2019)

Statistical and Computational Rates in Graph Logistic Regression. - Quentin Berthet; Nicolai Baldin (AISTATS, 2020)

Stochastic Optimization for Regularized Wasserstein Estimators. - Marin Ballu; Quentin Berthet; Francis R. Bach (ICML, 2020)

Fast Differentiable Sorting and Ranking. - Mathieu Blondel; Olivier Teboul; Quentin Berthet; Josip Djolonga (ICML, 2020)

Learning with Differentiable Pertubed Optimizers. - Quentin Berthet; Mathieu Blondel; Olivier Teboul; Marco Cuturi; Jean-Philippe Vert; Francis R. Bach (NeurIPS, 2020)

Learning with Differentiable Perturbed Optimizers. - Quentin Berthet; Mathieu Blondel; Olivier Teboul; Marco Cuturi; Jean-Philippe Vert; Francis R. Bach (CoRR, 2020)

An Area-Efficient SPHINCS+ Post-Quantum Signature Coprocessor. - Quentin Berthet; Andres Upegui; Laurent Gantel; Alexandre Duc; Giulia Traverso (IPDPS Workshops, 2021)

Self-Supervised Learning of Audio Representations From Permutations With Differentiable Ranking. - Andrew N. Carr; Quentin Berthet; Mathieu Blondel; Olivier Teboul; Neil Zeghidour (IEEE Signal Process. Lett., 2021)

Efficient and Modular Implicit Differentiation. - Mathieu Blondel; Quentin Berthet; Marco Cuturi; Roy Frostig; Stephan Hoyer; Felipe Llinares-López; Fabian Pedregosa; Jean-Philippe Vert (NeurIPS, 2022)

Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. - Benjamin Dubois-Taine; Francis R. Bach; Quentin Berthet; Adrien B. Taylor (NeurIPS, 2022)

A unified software/hardware scalable architecture for brain-inspired computing based on self-organizing neural models. - Artem R. Muliukov; Laurent Rodriguez; Benoît Miramond; Lyes Khacef; Joachim Schmidt 004; Quentin Berthet; Andres Upegui (CoRR, 2022)

Regression as Classification: Influence of Task Formulation on Neural Network Features. - Lawrence Stewart; Francis R. Bach; Quentin Berthet; Jean-Philippe Vert (AISTATS, 2023)

Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes. - Marin Ballu; Quentin Berthet (ICML, 2023)

Differentiable Clustering with Perturbed Spanning Forests. - Lawrence Stewart; Francis R. Bach; Felipe Llinares-López; Quentin Berthet (NeurIPS, 2023)

Decoding-time Realignment of Language Models. - Tianlin Liu; Shangmin Guo; Leonardo Bianco; Daniele Calandriello; Quentin Berthet; Felipe Llinares-López; Jessica Hoffmann; Lucas Dixon; Michal Valko; Mathieu Blondel (ICML, 2024)

Implicit Diffusion: Efficient optimization through stochastic sampling. - Pierre Marion; Anna Korba; Peter L. Bartlett; Mathieu Blondel; Valentin De Bortoli; Arnaud Doucet; Felipe Llinares-López; Courtney Paquette; Quentin Berthet (AISTATS, 2025)

Soft Condorcet Optimization for Ranking of General Agents. - Marc Lanctot; Kate Larson; Michael Kaisers; Quentin Berthet; Ian Gemp; Manfred Diaz; Roberto-Rafael Maura-Rivero; Yoram Bachrach; Anna Koop; Doina Precup (AAMAS, 2025)

Building Bridges between Regression, Clustering, and Classification. - Lawrence Stewart; Francis R. Bach; Quentin Berthet (CoRR, 2025)