• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 118 matches

• 2023
• 
  Peter L. Bartlett, Philip M. Long, Olivier Bousquet:
  The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima. J. Mach. Learn. Res. 24: 316:1-316:36 (2023)
• 
  Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya O. Tolstikhin:
  Fine-Grained Distribution-Dependent Learning Curves. COLT 2023: 5890-5924
• 
  Andrew Drozdov, Nathanael Schärli, Ekin Akyürek, Nathan Scales, Xinying Song, Xinyun Chen, Olivier Bousquet, Denny Zhou:
  Compositional Semantic Parsing with Large Language Models. ICLR 2023
• 
  Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi:
  Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR 2023
• 
  Noga Alon, Olivier Bousquet, Kasper Green Larsen, Shay Moran, Shlomo Moran:
  Diagonalization Games. CoRR abs/2301.01924 (2023)
• 
  Noga Alon, Olivier Bousquet, Kasper Green Larsen, Shay Moran, Shlomo Moran:
  Diagonalization Games. Electron. Colloquium Comput. Complex. TR23 (2023)
• 2022
• 
  Olivier Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer:
  Monotone Learning. COLT 2022: 842-866
• 
  Olivier Bousquet, Amit Daniely, Haim Kaplan, Yishay Mansour, Shay Moran, Uri Stemmer:
  Monotone Learning. CoRR abs/2202.05246 (2022)
• 
  Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi:
  Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. CoRR abs/2205.10625 (2022)
• 
  Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya O. Tolstikhin:
  Fine-Grained Distribution-Dependent Learning Curves. CoRR abs/2208.14615 (2022)
• 
  Andrew Drozdov, Nathanael Schärli, Ekin Akyürek, Nathan Scales, Xinying Song, Xinyun Chen, Olivier Bousquet, Denny Zhou:
  Compositional Semantic Parsing with Large Language Models. CoRR abs/2209.15003 (2022)
• 
  Peter L. Bartlett, Philip M. Long, Olivier Bousquet:
  The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima. CoRR abs/2210.01513 (2022)
• 
  Olivier Bousquet, Haim Kaplan, Aryeh Kontorovich, Yishay Mansour, Shay Moran, Menachem Sadigurschi, Uri Stemmer:
  Differentially-Private Bayes Consistency. CoRR abs/2212.04216 (2022)
• 2021
• 
  Olivier Bernardi, Mireille Bousquet-Mélou, Kilian Raschel:
  Counting quadrant walks via Tutte's invariant method. Comb. Theory 1(0) (2021)
• 
  Vincent Cassé, Raymond Armante, Philippe Bousquet, Olivier Chomette, Cyril Crevoisier, Thibault Delahaye, Dimitri Edouart, Fabien Gibert, Bruno Millet, Frédéric Nahan, Clémence Pierangelo:
  Development and Validation of an End-to-End Simulator and Gas Concentration Retrieval Processor Applied to the MERLIN Lidar Mission. Remote. Sens. 13(14): 2679 (2021)
• 
  Olivier Bousquet, Mark Braverman, Gillat Kol, Klim Efremenko, Shay Moran:
  Statistically Near-Optimal Hypothesis Selection. FOCS 2021: 909-919
• 
  Olivier Bousquet, Steve Hanneke, Shay Moran, Ramon van Handel, Amir Yehudayoff:
  A theory of universal learning. STOC 2021: 532-541
• 
  Olivier Bousquet, Mark Braverman, Klim Efremenko, Gillat Kol, Shay Moran:
  Statistically Near-Optimal Hypothesis Selection. CoRR abs/2108.07880 (2021)
• 2020
• 
  Karol Kurach, Anton Raichuk, Piotr Stanczyk, Michal Zajac, Olivier Bachem, Lasse Espeholt, Carlos Riquelme, Damien Vincent, Marcin Michalski, Olivier Bousquet, Sylvain Gelly:
  Google Research Football: A Novel Reinforcement Learning Environment. AAAI 2020: 4501-4510
• 
  Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly:
  Precision-Recall Curves Using Information Divergence Frontiers. AISTATS 2020: 2550-2559
• 
  Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy:
  Proper Learning, Helly Number, and an Optimal SVM Bound. COLT 2020: 582-609
• 
  Olivier Bousquet, Yegor Klochkov, Nikita Zhivotovskiy:
  Sharper Bounds for Uniformly Stable Algorithms. COLT 2020: 610-626
• 
  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:
  Measuring Compositional Generalization: A Comprehensive Method on Realistic Data. ICLR 2020
• 
  Olivier Bousquet, Roi Livni, Shay Moran:
  Synthetic Data Generators - Sequential and Private. NeurIPS 2020
• 
  Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers:
  What Do Neural Networks Learn When Trained With Random Labels? NeurIPS 2020
• 
  Thomas Unterthiner, Daniel Keysers, Sylvain Gelly, Olivier Bousquet, Ilya O. Tolstikhin:
  Predicting Neural Network Accuracy from Weights. CoRR abs/2002.11448 (2020)
• 
  Olivier Bousquet, Steve Hanneke, Shay Moran, Nikita Zhivotovskiy:
  Proper Learning, Helly Number, and an Optimal SVM Bound. CoRR abs/2005.11818 (2020)
• 
  Hartmut Maennel, Ibrahim M. Alabdulmohsin, Ilya O. Tolstikhin, Robert J. N. Baldock, Olivier Bousquet, Sylvain Gelly, Daniel Keysers:
  What Do Neural Networks Learn When Trained With Random Labels? CoRR abs/2006.10455 (2020)
• 
  Olivier Bousquet, Steve Hanneke, Shay Moran, Ramon van Handel, Amir Yehudayoff:
  A Theory of Universal Learning. CoRR abs/2011.04483 (2020)
• 2019
• 
  Olivier Bousquet, Daniel Kane, Shay Moran:
  The Optimal Approximation Factor in Density Estimation. COLT 2019: 318-341

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