Quentin Berthet
Quentin Berthet
Google Research, Brain team Paris
Email verificata su google.com - Home page
Titolo
Citata da
Citata da
Anno
Complexity theoretic lower bounds for sparse principal component detection
Q Berthet, P Rigollet
Conference on Learning Theory, 1046-1066, 2013
308*2013
Optimal detection of sparse principal components in high dimension
Q Berthet, P Rigollet
The Annals of Statistics 41 (4), 1780-1815, 2013
2622013
Statistical and computational trade-offs in estimation of sparse principal components
T Wang, Q Berthet, RJ Samworth
The Annals of Statistics 44 (5), 1896-1930, 2016
1122016
Unsupervised alignment of embeddings with Wasserstein Procrustes
E Grave, A Joulin, Q Berthet
International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 2018
902018
Learning with differentiable perturbed optimizers
Q Berthet, M Blondel, O Teboul, M Cuturi, JP Vert, F Bach
NeurIPS 2020, 2020
362020
Exact recovery in the Ising blockmodel
Q Berthet, P Rigollet, P Srivastava
The Annals of Statistics 47 (4), 1805 - 1834, 2016
342016
Estimation of smooth densities in Wasserstein distance
J Weed, Q Berthet
Proceedings of the Thirty-Second Conference on Learning Theory, COLT 2019, 2019
312019
Fast differentiable sorting and ranking
M Blondel, O Teboul, Q Berthet, J Djolonga
International Conference on Machine Learning, 950-959, 2020
302020
Average-case hardness of RIP certification
T Wang, Q Berthet, Y Plan
Advances in Neural Information Processing Systems, NeurIPS 2016, 2016
302016
Fast rates for bandit optimization with Upper-Confidence Frank-Wolfe
Q Berthet, V Perchet
Advances in Neural Information Processing Systems, NeurIPS 2017, 2017
252017
Statistical and computational rates in graph logistic regression
Q Berthet, N Baldin
International Conference on Artificial Intelligence and Statistics, 2719-2730, 2020
14*2020
Resource allocation for statistical estimation
Q Berthet, V Chandrasekaran
Proceedings of the IEEE 104 (1), 111-125, 2015
142015
Stochastic optimization for regularized Wasserstein estimators
M Ballu, Q Berthet, F Bach
International Conference on Machine Learning, 602-612, 2020
92020
Detection of planted solutions for flat satisfiability problems
Q Berthet, JS Ellenberg
International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 2015
9*2015
Noisy adaptive group testing using Bayesian sequential experimental design
M Cuturi, O Teboul, Q Berthet, A Doucet, JP Vert
arXiv preprint arXiv:2004.12508, 2020
82020
Optimal testing for planted satisfiability problems
Q Berthet
Electronic Journal of Statistics 9 (1), 298-317, 2015
82015
Regularized contextual bandits
X Fontaine, Q Berthet, V Perchet
International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 2018
62018
Statistical windows in testing for the initial distribution of a reversible Markov chain
Q Berthet, V Kanade
International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 2018
52018
Self-Supervised Learning of Audio Representations From Permutations With Differentiable Ranking
AN Carr, Q Berthet, M Blondel, O Teboul, N Zeghidour
IEEE Signal Processing Letters 28, 708-712, 2021
12021
Efficient and Modular Implicit Differentiation
M Blondel, Q Berthet, M Cuturi, R Frostig, S Hoyer, F Llinares-Lpez, ...
arXiv preprint arXiv:2105.15183, 2021
2021
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
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