Olivier Bousquet

100 papers A* 23A 3B 1Misc 1Journal 50Unranked 21

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Evaluation of retrieval-based QA on QUEST-LOFT. CoRR Nathan Scales, Nathanael Schärli, Olivier Bousquet
2024	J	`jnl`	Diagonalization Games. Am. Math. Mon. Noga Alon, Olivier Bousquet, Kasper Green Larsen, Shay Moran, Shlomo Moran
2023	A*	`conf`	Compositional Semantic Parsing with Large Language Models. ICLR Andrew Drozdov, Nathanael Schärli, Ekin Akyürek, Nathan Scales, Xinying Song, Xinyun Chen, Olivier Bousquet, Denny Zhou
2023	J	`jnl`	Diagonalization Games. CoRR Noga Alon, Olivier Bousquet, Kasper Green Larsen, Shay Moran, Shlomo Moran
2023	J	`jnl`	Diagonalization Games. Electron. Colloquium Comput. Complex. Noga Alon, Olivier Bousquet, Kasper Green Larsen, Shay Moran, Shlomo Moran
2023	A*	`conf`	Fine-Grained Distribution-Dependent Learning Curves. COLT Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya O. Tolstikhin
2023	A*	`conf`	Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi
2023	J	`jnl`	The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima. J. Mach. Learn. Res. Peter L. Bartlett, Philip M. Long, Olivier Bousquet
2022	J	`jnl`	Compositional Semantic Parsing with Large Language Models. CoRR Andrew Drozdov, Nathanael Schärli, Ekin Akyürek, Nathan Scales, Xinying Song, Xinyun Chen, Olivier Bousquet, Denny Zhou
2022	J	`jnl`	Differentially-Private Bayes Consistency. CoRR Olivier Bousquet, Haim Kaplan, Aryeh Kontorovich, Yishay Mansour, Shay Moran, Menachem Sadigurschi, Uri Stemmer
2022	J	`jnl`	Fine-Grained Distribution-Dependent Learning Curves. CoRR Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya O. Tolstikhin
2022	J	`jnl`	Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. CoRR Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi
2022	A*	`conf`	Monotone Learning. COLT Olivier Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer
2022	J	`jnl`	Monotone Learning. CoRR Olivier Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer
2022	J	`jnl`	The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima. CoRR Peter L. Bartlett, Philip M. Long, Olivier Bousquet
2021	A*	`conf`	A theory of universal learning. STOC Olivier Bousquet, Steve Hanneke, Shay Moran, Ramon van Handel, Amir Yehudayoff
2021	A*	`conf`	Statistically Near-Optimal Hypothesis Selection. FOCS Olivier Bousquet, Mark Braverman, Gillat Kol, Klim Efremenko, Shay Moran
2021	J	`jnl`	Statistically Near-Optimal Hypothesis Selection. CoRR Olivier Bousquet, Mark Braverman, Klim Efremenko, Gillat Kol, Shay Moran
2020	J	`jnl`	A Theory of Universal Learning. CoRR Olivier Bousquet, Steve Hanneke, Shay Moran, Ramon van Handel, Amir Yehudayoff
2020	A*	`conf`	Google Research Football: A Novel Reinforcement Learning Environment. AAAI Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly
2020	A*	`conf`	Measuring Compositional Generalization: A Comprehensive Method on Realistic Data. ICLR 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
2020	A	`conf`	Precision-Recall Curves Using Information Divergence Frontiers. AISTATS Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly
2020	J	`jnl`	Predicting Neural Network Accuracy from Weights. CoRR Thomas Unterthiner, Daniel Keysers, Sylvain Gelly, Olivier Bousquet, Ilya O. Tolstikhin
2020	A*	`conf`	Proper Learning, Helly Number, and an Optimal SVM Bound. COLT Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy
2020	J	`jnl`	Proper Learning, Helly Number, and an Optimal SVM Bound. CoRR Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy
2020	A*	`conf`	Sharper Bounds for Uniformly Stable Algorithms. COLT Olivier Bousquet, Yegor Klochkov, Nikita Zhivotovskiy
2020	A*	`conf`	Synthetic Data Generators - Sequential and Private. NeurIPS Olivier Bousquet, Roi Livni, Shay Moran
2020	A*	`conf`	What Do Neural Networks Learn When Trained With Random Labels? NeurIPS Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers
2020	J	`jnl`	What Do Neural Networks Learn When Trained With Random Labels? CoRR Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers
2019	J	`jnl`	Evaluating Generative Models Using Divergence Frontiers. CoRR Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly
2019	J	`jnl`	Fast classification rates without standard margin assumptions. CoRR Olivier Bousquet, Nikita Zhivotovskiy
2019	J	`jnl`	Google Research Football: A Novel Reinforcement Learning Environment. CoRR Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly
2019	J	`jnl`	Measuring Compositional Generalization: A Comprehensive Method on Realistic Data. CoRR 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
2019	J	`jnl`	Passing Tests without Memorizing: Two Models for Fooling Discriminators. CoRR Olivier Bousquet, Roi Livni, Shay Moran
2019	A*	`conf`	Practical and Consistent Estimation of f-Divergences. NeurIPS Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
2019	J	`jnl`	Practical and Consistent Estimation of f-Divergences. CoRR Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
2019	J	`jnl`	Sharper bounds for uniformly stable algorithms. CoRR Olivier Bousquet, Yegor Klochkov, Nikita Zhivotovskiy
2019	A*	`conf`	The Optimal Approximation Factor in Density Estimation. COLT Olivier Bousquet, Daniel Kane, Shay Moran
2019	J	`jnl`	The Optimal Approximation Factor in Density Estimation. CoRR Olivier Bousquet, Daniel Kane, Shay Moran
2019	J	`jnl`	The Visual Task Adaptation Benchmark. CoRR Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby
2019	A*	`conf`	When can unlabeled data improve the learning rate? COLT Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner
2019	J	`jnl`	When can unlabeled data improve the learning rate? CoRR Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner
2018	A*	`conf`	Are GANs Created Equal? A Large-Scale Study. NeurIPS Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet
2018	A*	`conf`	Assessing Generative Models via Precision and Recall. NeurIPS Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, Sylvain Gelly
2018	J	`jnl`	Assessing Generative Models via Precision and Recall. CoRR Mehdi S. M. Sajjadi, Olivier Bachem, Mario Lucic, Olivier Bousquet, Sylvain Gelly
2018	J	`jnl`	Gradient Descent Quantizes ReLU Network Features. CoRR Hartmut Maennel, Olivier Bousquet, Sylvain Gelly
2018	—	`conf`	Wasserstein Auto-Encoders. ICLR Ilya O. Tolstikhin, Olivier Bousquet, Sylvain Gelly, Bernhard Schölkopf
2017	—	`conf`	AdaGAN: Boosting Generative Models. NIPS Ilya O. Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, Bernhard Schölkopf
2017	J	`jnl`	AdaGAN: Boosting Generative Models. CoRR Ilya O. Tolstikhin, Sylvain Gelly, Olivier Bousquet, Carl-Johann Simon-Gabriel, Bernhard Schölkopf
2017	—	`conf`	Approximation and Convergence Properties of Generative Adversarial Learning. NIPS Shuang Liu, Olivier Bousquet, Kamalika Chaudhuri
2017	J	`jnl`	Approximation and Convergence Properties of Generative Adversarial Learning. CoRR Shuang Liu, Olivier Bousquet, Kamalika Chaudhuri
2017	J	`jnl`	Are GANs Created Equal? A Large-Scale Study. CoRR Mario Lucic, Karol Kurach, Marcin Michalski, Sylvain Gelly, Olivier Bousquet
2017	J	`jnl`	Better Text Understanding Through Image-To-Text Transfer. CoRR Karol Kurach, Sylvain Gelly, Michal Jastrzebski, Philip Häusser, Olivier Teytaud, Damien Vincent, Olivier Bousquet
2017	J	`jnl`	Critical Hyper-Parameters: No Random, No Cry. CoRR Olivier Bousquet, Sylvain Gelly, Karol Kurach, Olivier Teytaud, Damien Vincent
2017	J	`jnl`	Toward Optimal Run Racing: Application to Deep Learning Calibration. CoRR Olivier Bousquet, Sylvain Gelly, Karol Kurach, Marc Schoenauer, Michèle Sebag, Olivier Teytaud, Damien Vincent
2017	J	`jnl`	Wasserstein Auto-Encoders. CoRR Ilya O. Tolstikhin, Olivier Bousquet, Sylvain Gelly, Bernhard Schölkopf
2010	J	`jnl`	L'apprentissage statistique à grande échelle. Monde des Util. Anal. Données Léon Bottou, Olivier Bousquet
2009	J	`jnl`	Prototype Classification: Insights from Machine Learning. Neural Comput. Arnulf B. A. Graf, Olivier Bousquet, Gunnar Rätsch, Bernhard Schölkopf
2007	J	`jnl`	Combining PAC-Bayesian and Generic Chaining Bounds. J. Mach. Learn. Res. Jean-Yves Audibert, Olivier Bousquet
2007	J	`jnl`	Guest editorial: Learning theory. Mach. Learn. Olivier Bousquet, André Elisseeff
2007	—	`conf`	Learning using Large Datasets. NATO ASI Mining Massive Data Sets for Security Léon Bottou, Olivier Bousquet
2007	J	`jnl`	Statistical properties of kernel principal component analysis. Mach. Learn. Gilles Blanchard, Olivier Bousquet, Laurent Zwald
2007	—	`conf`	The Tradeoffs of Large Scale Learning. NIPS Léon Bottou, Olivier Bousquet
2006	—	`conf`	Cascade Evaluation of Clustering Algorithms. ECML Laurent Candillier, Isabelle Tellier, Fabien Torre, Olivier Bousquet
2005	—	`conf`	Evaluating Predictive Uncertainty Challenge. MLCW Joaquin Quiñonero Candela, Carl Edward Rasmussen, Fabian H. Sinz, Olivier Bousquet, Bernhard Schölkopf
2005	A	`conf`	Hilbertian Metrics and Positive Definite Kernels on Probability Measures. AISTATS Matthias Hein, Olivier Bousquet
2005	Misc	`conf`	Joint Kernel Maps. IWANN Jason Weston, Bernhard Schölkopf, Olivier Bousquet
2005	A	`conf`	Kernel Constrained Covariance for Dependence Measurement. AISTATS Arthur Gretton, Alexander J. Smola, Olivier Bousquet, Ralf Herbrich, Andrei Belitski, Mark Augath, Yusuke Murayama, Jon Pauls, Bernhard Schölkopf, Nikos K. Logothetis
2005	J	`jnl`	Kernel Methods for Measuring Independence. J. Mach. Learn. Res. Arthur Gretton, Ralf Herbrich, Alexander J. Smola, Olivier Bousquet, Bernhard Schölkopf
2005	J	`jnl`	Maximal margin classification for metric spaces. J. Comput. Syst. Sci. Matthias Hein, Olivier Bousquet, Bernhard Schölkopf
2005	B	`conf`	Measuring Statistical Dependence with Hilbert-Schmidt Norms. ALT Arthur Gretton, Olivier Bousquet, Alexander J. Smola, Bernhard Schölkopf
2005	—	`conf`	SSC: Statistical Subspace Clustering. MLDM Laurent Candillier, Isabelle Tellier, Fabien Torre, Olivier Bousquet
2005	—	`conf`	SSC: statistical subspace clustering. EGC Laurent Candillier, Isabelle Tellier, Fabien Torre, Olivier Bousquet
2004	J	`jnl`	A Compression Approach to Support Vector Model Selection. J. Mach. Learn. Res. Ulrike von Luxburg, Olivier Bousquet, Bernhard Schölkopf
2004	—	`ed.`	Advanced Lectures on Machine Learning, ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003, Revised Lectures Advanced Lectures on Machine Learning Olivier Bousquet, Ulrike von Luxburg, Gunnar Rätsch
2004	J	`jnl`	Distance-Based Classification with Lipschitz Functions. J. Mach. Learn. Res. Ulrike von Luxburg, Olivier Bousquet
2004	—	`conf`	Hilbertian Metrics on Probability Measures and Their Application in SVM?s. DAGM-Symposium Matthias Hein, Thomas Navin Lal, Olivier Bousquet
2004	J	`jnl`	Kernel methods and their potential use in signal processing. IEEE Signal Process. Mag. Fernando Pérez-Cruz, Olivier Bousquet
2004	—	`conf`	Limits of Spectral Clustering. NIPS Ulrike von Luxburg, Olivier Bousquet, Mikhail Belkin
2004	A*	`conf`	On the Convergence of Spectral Clustering on Random Samples: The Normalized Case. COLT Ulrike von Luxburg, Olivier Bousquet, Mikhail Belkin
2004	A*	`conf`	Statistical Properties of Kernel Principal Component Analysis. COLT Laurent Zwald, Olivier Bousquet, Gilles Blanchard
2003	—	`conf`	Concentration Inequalities. Advanced Lectures on Machine Learning Stéphane Boucheron, Gábor Lugosi, Olivier Bousquet
2003	A*	`conf`	Distance-Based Classification with Lipschitz Functions. COLT Ulrike von Luxburg, Olivier Bousquet
2003	J	`jnl`	Feature selection and transduction for prediction of molecular bioactivity for drug design. Bioinform. Jason Weston, Fernando Pérez-Cruz, Olivier Bousquet, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf
2003	—	`conf`	Introduction to Statistical Learning Theory. Advanced Lectures on Machine Learning Olivier Bousquet, Stéphane Boucheron, Gábor Lugosi
2003	—	`conf`	Kernel methods and their applications to signal processing. ICASSP (4) Olivier Bousquet, Fernando Pérez-Cruz
2003	—	`conf`	Learning with Local and Global Consistency. NIPS Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf
2003	A*	`conf`	Maximal Margin Classification for Metric Spaces. COLT Matthias Hein, Olivier Bousquet
2003	—	`conf`	Measure Based Regularization. NIPS Olivier Bousquet, Olivier Chapelle, Matthias Hein
2003	—	`conf`	PAC-Bayesian Generic Chaining. NIPS Jean-Yves Audibert, Olivier Bousquet
2003	—	`conf`	Ranking on Data Manifolds. NIPS Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf
2002	J	`jnl`	Choosing Multiple Parameters for Support Vector Machines. Mach. Learn. Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet, Sayan Mukherjee
2002	A*	`conf`	Localized Rademacher Complexities. COLT Peter L. Bartlett, Olivier Bousquet, Shahar Mendelson
2002	—	`conf`	On the Complexity of Learning the Kernel Matrix. NIPS Olivier Bousquet, Daniel J. L. Herrmann
2002	A*	`conf`	Some Local Measures of Complexity of Convex Hulls and Generalization Bounds. COLT Olivier Bousquet, Vladimir Koltchinskii, Dmitriy Panchenko
2002	J	`jnl`	Stability and Generalization. J. Mach. Learn. Res. Olivier Bousquet, André Elisseeff
2002	J	`jnl`	Tracking a Small Set of Experts by Mixing Past Posteriors. J. Mach. Learn. Res. Olivier Bousquet, Manfred K. Warmuth
2001	—	`conf`	Tracking a Small Set of Experts by Mixing Past Posteriors. COLT/EuroCOLT Olivier Bousquet, Manfred K. Warmuth
2000	—	`conf`	Algorithmic Stability and Generalization Performance. NIPS Olivier Bousquet, André Elisseeff
1999	J	`jnl`	Spatial Learning and Localization in Rodents: A Computational Model of the Hippocampus and its Implications for Mobile Robots. Adapt. Behav. Karthik Balakrishnan, Olivier Bousquet, Vasant G. Honavar