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Quentin Berthet
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2020 – today
- 2024
- [c19]Tianlin Liu, Shangmin Guo, Leonardo Bianco, Daniele Calandriello, Quentin Berthet, Felipe Llinares-López, Jessica Hoffmann, Lucas Dixon, Michal Valko, Mathieu Blondel:
Decoding-time Realignment of Language Models. ICML 2024 - [i21]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 abs/2402.02992 (2024) - [i20]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 abs/2402.05468 (2024) - 2023
- [c18]Lawrence Stewart, Francis R. Bach, Quentin Berthet, Jean-Philippe Vert:
Regression as Classification: Influence of Task Formulation on Neural Network Features. AISTATS 2023: 11563-11582 - [c17]Marin Ballu, Quentin Berthet:
Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes. ICML 2023: 1595-1613 - [c16]Lawrence Stewart, Francis R. Bach, Felipe Llinares-López, Quentin Berthet:
Differentiable Clustering with Perturbed Spanning Forests. NeurIPS 2023 - [i19]Lawrence Stewart, Francis R. Bach, Felipe Llinares-López, Quentin Berthet:
Differentiable Clustering with Perturbed Spanning Forests. CoRR abs/2305.16358 (2023) - 2022
- [c15]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 - [c14]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 - [i18]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 abs/2201.02262 (2022) - [i17]Benjamin Dubois-Taine, Francis R. Bach, Quentin Berthet, Adrien B. Taylor:
Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization. CoRR abs/2205.12751 (2022) - [i16]Lawrence Stewart, Francis R. Bach, Quentin Berthet, Jean-Philippe Vert:
Regression as Classification: Influence of Task Formulation on Neural Network Features. CoRR abs/2211.05641 (2022) - [i15]Marin Ballu, Quentin Berthet:
Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes. CoRR abs/2211.10420 (2022) - 2021
- [j2]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: 708-712 (2021) - [c13]Quentin Berthet, Andres Upegui
An Area-Efficient SPHINCS+ Post-Quantum Signature Coprocessor. IPDPS Workshops 2021: 180-187 - [i14]Andrew N. Carr, Quentin Berthet, Mathieu Blondel, Olivier Teboul, Neil Zeghidour:
Self-Supervised Learning of Audio Representations from Permutations with Differentiable Ranking. CoRR abs/2103.09879 (2021) - [i13]Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert:
Efficient and Modular Implicit Differentiation. CoRR abs/2105.15183 (2021) - 2020
- [c12]Quentin Berthet, Nicolai Baldin:
Statistical and Computational Rates in Graph Logistic Regression. AISTATS 2020: 2719-2730 - [c11]Marin Ballu, Quentin Berthet, Francis R. Bach:
Stochastic Optimization for Regularized Wasserstein Estimators. ICML 2020: 602-612 - [c10]Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga:
Fast Differentiable Sorting and Ranking. ICML 2020: 950-959 - [c9]Quentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, Francis R. Bach:
Learning with Differentiable Pertubed Optimizers. NeurIPS 2020 - [i12]Quentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, Francis R. Bach:
Learning with Differentiable Perturbed Optimizers. CoRR abs/2002.08676 (2020) - [i11]Marin Ballu, Quentin Berthet, Francis R. Bach:
Stochastic Optimization for Regularized Wasserstein Estimators. CoRR abs/2002.08695 (2020) - [i10]Mathieu Blondel, Olivier Teboul, Quentin Berthet, Josip Djolonga:
Fast Differentiable Sorting and Ranking. CoRR abs/2002.08871 (2020)
2010 – 2019
- 2019
- [c8]Quentin Berthet, Varun Kanade:
Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain. AISTATS 2019: 246-255 - [c7]Quentin Berthet, Jordan S. Ellenberg:
Detection of Planted Solutions for Flat Satisfiability Problems. AISTATS 2019: 1303-1312 - [c6]Edouard Grave, Armand Joulin, Quentin Berthet:
Unsupervised Alignment of Embeddings with Wasserstein Procrustes. AISTATS 2019: 1880-1890 - [c5]Xavier Fontaine, Quentin Berthet, Vianney Perchet:
Regularized Contextual Bandits. AISTATS 2019: 2144-2153 - [c4]Jonathan Weed, Quentin Berthet:
Estimation of smooth densities in Wasserstein distance. COLT 2019: 3118-3119 - 2018
- [i9]Edouard Grave, Armand Joulin, Quentin Berthet:
Unsupervised Alignment of Embeddings with Wasserstein Procrustes. CoRR abs/1805.11222 (2018) - [i8]Quentin Berthet, Varun Kanade:
Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain. CoRR abs/1808.01857 (2018) - [i7]Xavier Fontaine, Quentin Berthet, Vianney Perchet:
Regularized Contextual Bandits. CoRR abs/1810.05065 (2018) - 2017
- [c3]Quentin Berthet, Vianney Perchet:
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe. NIPS 2017: 2225-2234 - [i6]Quentin Berthet, Vianney Perchet:
Bandit Optimization with Upper-Confidence Frank-Wolfe. CoRR abs/1702.06917 (2017) - 2016
- [j1]Quentin Berthet, Venkat Chandrasekaran:
Resource Allocation for Statistical Estimation. Proc. IEEE 104(1): 111-125 (2016) - [c2]Tengyao Wang, Quentin Berthet, Yaniv Plan:
Average-case hardness of RIP certification. NIPS 2016: 3819-3827 - [i5]Tengyao Wang, Quentin Berthet, Yaniv Plan:
Average-case Hardness of RIP Certification. CoRR abs/1605.09646 (2016) - [i4]Quentin Berthet, Philippe Rigollet, Piyush Srivastava:
Exact recovery in the Ising blockmodel. CoRR abs/1612.03880 (2016) - 2015
- [i3]Quentin Berthet, Jordan S. Ellenberg:
Detection of Planted Solutions for Flat Satisfiability Problems. CoRR abs/1502.06144 (2015) - 2014
- [b1]Quentin Berthet:
Statistical and Computational Tradeoffs in High-dimensional Problems. Princeton University, USA, 2014 - [i2]Quentin Berthet:
Optimal Testing for Planted Satisfiability Problems. CoRR abs/1401.2205 (2014) - 2013
- [c1]Quentin Berthet, Philippe Rigollet:
Complexity Theoretic Lower Bounds for Sparse Principal Component Detection. COLT 2013: 1046-1066 - [i1]Quentin Berthet, Philippe Rigollet:
Computational Lower Bounds for Sparse PCA. CoRR abs/1304.0828 (2013)
Coauthor Index
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last updated on 2024-09-04 00:30 CEST by the dblp team
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