Bousquet, Olivier

47 publications

ICLR 2023 Compositional Semantic Parsing with Large Language Models Andrew Drozdov, Nathanael Schärli, Ekin Akyürek, Nathan Scales, Xinying Song, Xinyun Chen, Olivier Bousquet, Denny Zhou

COLT 2023 Fine-Grained Distribution-Dependent Learning Curves Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya Tolstikhin

ICLR 2023 Least-to-Most Prompting Enables Complex Reasoning in Large Language Models Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V Le, Ed H. Chi

JMLR 2023 The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima Peter L. Bartlett, Philip M. Long, Olivier Bousquet

AAAI 2020 Google Research Football: A Novel Reinforcement Learning Environment Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly

ICLR 2020 Measuring Compositional Generalization: A Comprehensive Method on Realistic Data Daniel Keysers, Nathanael Schärli, Nathan Scales, Hylke Buisman, Daniel Furrer, Sergii Kashubin, Nikola Momchev, Danila Sinopalnikov, Lukasz Stafiniak, Tibor Tihon, Dmitry Tsarkov, Xiao Wang, Marc van Zee, Olivier Bousquet

AISTATS 2020 Precision-Recall Curves Using Information Divergence Frontiers Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly

COLT 2020 Proper Learning, Helly Number, and an Optimal SVM Bound Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy

COLT 2020 Sharper Bounds for Uniformly Stable Algorithms Olivier Bousquet, Yegor Klochkov, Nikita Zhivotovskiy

NeurIPS 2020 Synthetic Data Generators -- Sequential and Private Olivier Bousquet, Roi Livni, Shay Moran

NeurIPS 2020 What Do Neural Networks Learn When Trained with Random Labels? Hartmut Maennel, Ibrahim M Alabdulmohsin, Ilya O Tolstikhin, Robert Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers

NeurIPS 2019 Practical and Consistent Estimation of F-Divergences Paul Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O Tolstikhin

COLT 2019 The Optimal Approximation Factor in Density Estimation Olivier Bousquet, Daniel Kane, Shay Moran

COLT 2019 When Can Unlabeled Data Improve the Learning Rate? Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya Tolstikhin, Ruth Urner

NeurIPS 2018 Are GANs Created Equal? a Large-Scale Study Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet

NeurIPS 2018 Assessing Generative Models via Precision and Recall Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, Sylvain Gelly

ICLR 2018 Wasserstein Auto-Encoders Ilya Tolstikhin, Olivier Bousquet, Sylvain Gelly, Bernhard Schoelkopf

NeurIPS 2017 AdaGAN: Boosting Generative Models Ilya O Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, Bernhard Schölkopf

NeurIPS 2017 Approximation and Convergence Properties of Generative Adversarial Learning Shuang Liu, Olivier Bousquet, Kamalika Chaudhuri

JMLR 2007 Combining PAC-Bayesian and Generic Chaining Bounds Jean-Yves Audibert, Olivier Bousquet

MLJ 2007 Guest Editorial: Learning Theory Olivier Bousquet, André Elisseeff

MLJ 2007 Statistical Properties of Kernel Principal Component Analysis Gilles Blanchard, Olivier Bousquet, Laurent Zwald

NeurIPS 2007 The Tradeoffs of Large Scale Learning Léon Bottou, Olivier Bousquet

ECML-PKDD 2006 Cascade Evaluation of Clustering Algorithms Laurent Candillier, Isabelle Tellier, Fabien Torre, Olivier Bousquet

AISTATS 2005 Hilbertian Metrics and Positive Definite Kernels on Probability Measures Matthias Hein, Olivier Bousquet

AISTATS 2005 Kernel Constrained Covariance for Dependence Measurement Arthur Gretton, Alexander Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schölkopf, Nikos Logothetis

JMLR 2005 Kernel Methods for Measuring Independence Arthur Gretton, Ralf Herbrich, Alexander Smola, Olivier Bousquet, Bernhard Schölkopf

ALT 2005 Measuring Statistical Dependence with Hilbert-Schmidt Norms Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schölkopf

JMLR 2004 A Compression Approach to Support Vector Model Selection Ulrike von Luxburg, Olivier Bousquet, Bernhard Schölkopf

JMLR 2004 Distance-Based Classification with Lipschitz Functions (Special Topic on Learning Theory) Ulrike von Luxburg, Olivier Bousquet

NeurIPS 2004 Limits of Spectral Clustering Ulrike V. Luxburg, Olivier Bousquet, Mikhail Belkin

COLT 2004 On the Convergence of Spectral Clustering on Random Samples: The Normalized Case Ulrike von Luxburg, Olivier Bousquet, Mikhail Belkin

COLT 2004 Statistical Properties of Kernel Principal Component Analysis Laurent Zwald, Olivier Bousquet, Gilles Blanchard

COLT 2003 Distance-Based Classification with Lipschitz Functions Ulrike von Luxburg, Olivier Bousquet

NeurIPS 2003 Learning with Local and Global Consistency Dengyong Zhou, Olivier Bousquet, Thomas N. Lal, Jason Weston, Bernhard Schölkopf

COLT 2003 Maximal Margin Classification for Metric Spaces Matthias Hein, Olivier Bousquet

NeurIPS 2003 Measure Based Regularization Olivier Bousquet, Olivier Chapelle, Matthias Hein

NeurIPS 2003 PAC-Bayesian Generic Chaining Jean-yves Audibert, Olivier Bousquet

NeurIPS 2003 Ranking on Data Manifolds Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf

MLJ 2002 Choosing Multiple Parameters for Support Vector Machines Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee

COLT 2002 Localized Rademacher Complexities Peter L. Bartlett, Olivier Bousquet, Shahar Mendelson

NeurIPS 2002 On the Complexity of Learning the Kernel Matrix Olivier Bousquet, Daniel Herrmann

COLT 2002 Some Local Measures of Complexity of Convex Hulls and Generalization Bounds Olivier Bousquet, Vladimir Koltchinskii, Dmitriy Panchenko

JMLR 2002 Stability and Generalization Olivier Bousquet, André Elisseeff

JMLR 2002 Tracking a Small Set of Experts by Mixing past Posteriors Olivier Bousquet, Manfred K. Warmuth

COLT 2001 Tracking a Small Set of Experts by Mixing past Posteriors Olivier Bousquet, Manfred K. Warmuth

NeurIPS 2000 Algorithmic Stability and Generalization Performance Olivier Bousquet, André Elisseeff