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Title
Cited by
Cited by
Year
Learning with local and global consistency
D Zhou, O Bousquet, T Lal, J Weston, B Schölkopf
Advances in neural information processing systems 16, 2003
52132003
Concentration inequalities
S Boucheron, G Lugosi, O Bousquet
Summer school on machine learning, 208-240, 2003
39092003
Choosing multiple parameters for support vector machines
O Chapelle, V Vapnik, O Bousquet, S Mukherjee
Machine learning 46, 131-159, 2002
33162002
The tradeoffs of large scale learning
L Bottou, O Bousquet
Advances in neural information processing systems 20, 2007
20752007
Stability and generalization
O Bousquet, A Elisseeff
The Journal of Machine Learning Research 2, 499-526, 2002
19112002
Measuring statistical dependence with Hilbert-Schmidt norms
A Gretton, O Bousquet, A Smola, B Schölkopf
International conference on algorithmic learning theory, 63-77, 2005
17422005
Are gans created equal? a large-scale study
M Lucic, K Kurach, M Michalski, S Gelly, O Bousquet
Advances in neural information processing systems 31, 2018
11002018
Wasserstein auto-encoders
I Tolstikhin, O Bousquet, S Gelly, B Schoelkopf
arXiv preprint arXiv:1711.01558, 2017
10802017
Ranking on data manifolds
D Zhou, J Weston, A Gretton, O Bousquet, B Schölkopf
Advances in neural information processing systems 16, 2003
9542003
Local rademacher complexities
PL Bartlett, O Bousquet, S Mendelson
8622005
Introduction to statistical learning theory
O Bousquet, S Boucheron, G Lugosi
Summer school on machine learning, 169-207, 2003
7802003
Theory of classification: A survey of some recent advances
S Boucheron, O Bousquet, G Lugosi
ESAIM: probability and statistics 9, 323-375, 2005
7382005
Consistency of spectral clustering
U Von Luxburg, M Belkin, O Bousquet
The Annals of Statistics, 555-586, 2008
7202008
Kernel methods for measuring independence
A Gretton, R Herbrich, A Smola, O Bousquet, B Schölkopf
MIT Press, 2005
4392005
Assessing generative models via precision and recall
MSM Sajjadi, O Bachem, M Lucic, O Bousquet, S Gelly
Advances in neural information processing systems 31, 2018
4242018
A Bennett concentration inequality and its application to suprema of empirical processes
O Bousquet
Comptes Rendus Mathematique 334 (6), 495-500, 2002
3762002
Adagan: Boosting generative models
IO Tolstikhin, S Gelly, O Bousquet, CJ Simon-Gabriel, B Schölkopf
Advances in neural information processing systems 30, 2017
2612017
Measuring compositional generalization: A comprehensive method on realistic data
D Keysers, N Schärli, N Scales, H Buisman, D Furrer, S Kashubin, ...
arXiv preprint arXiv:1912.09713, 2019
2602019
Least-to-most prompting enables complex reasoning in large language models
D Zhou, N Schärli, L Hou, J Wei, N Scales, X Wang, D Schuurmans, C Cui, ...
arXiv preprint arXiv:2205.10625, 2022
2382022
Google research football: A novel reinforcement learning environment
K Kurach, A Raichuk, P Stańczyk, M Zając, O Bachem, L Espeholt, ...
Proceedings of the AAAI conference on artificial intelligence 34 (04), 4501-4510, 2020
2332020
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