Bousquet, Olivier

1. Are GANs Created Equal? A Large-Scale Study
   2017/11/28 by Mario Lučić, Mario Lucic, Lucic, Mario +8 · 2 voices · 15 citations
   Computer Science · Mathematics · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Music and Audio Processing #Video Analysis and Summarization #cs.LG #stat.ML
2. Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
   2022/05/21 by Denny Zhou, Nathanael Schärli, Zhou, Denny +18 · 169 citations
   Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
3. Wasserstein Auto-Encoders
   2017/11/05 by Ilya Tolstikhin, Tolstikhin, Ilya, Olivier Bousquet +5 · 46 citations
   Computer Science · #Generative Adversarial Networks and Image Synthesis #Anomaly Detection Techniques and Applications #Human Pose and Action Recognition
4. Assessing Generative Models via Precision and Recall
   2018/05/31 by Mehdi S. M. Sajjadi, Sajjadi, Mehdi S. M., Olivier Bachem +7 · 39 citations
   Computer Science · #Generative Adversarial Networks and Image Synthesis #Data Visualization and Analytics #Anomaly Detection Techniques and Applications
5. Google Research Football: A Novel Reinforcement Learning Environment
   2019/07/25 by Kurach, Karol, Raichuk, Anton, Stańczyk, Piotr +8 · 27 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
6. A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark
   2019/10/01 by Zhai, Xiaohua, Puigcerver, Joan, Kolesnikov, Alexander +14 · 26 citations
   #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Measuring Compositional Generalization: A Comprehensive Method on Realistic Data
   2019/12/20 by Daniel Keysers, Keysers, Daniel, Nathanael Schärli +25 · 20 citations
   Computer Science · #Topic Modeling #Natural Language Processing Techniques #Multimodal Machine Learning Applications
8. From optimal transport to generative modeling: the VEGAN cookbook
   2017/05/22 by Bousquet, Olivier, Gelly, Sylvain, Tolstikhin, Ilya +2 · 7 citations
   #FOS: Computer and information sciences #Machine Learning (stat.ML)
9. Predicting Neural Network Accuracy from Weights
   2020/02/26 by Thomas Unterthiner, Unterthiner, Thomas, Daniel Keysers +7 · 10 citations
   Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
10. Gradient Descent Quantizes ReLU Network Features
    2018/03/22 by Hartmut Maennel, Maennel, Hartmut, Olivier Bousquet +3 · 8 citations
    Computer Science · #Stochastic Gradient Optimization Techniques #Adversarial Robustness in Machine Learning #Advanced Neural Network Applications
11. The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima
    2022/10/04 by Bartlett, Peter L., Long, Philip M., Bousquet, Olivier · 8 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
12. Sharper bounds for uniformly stable algorithms
    2019/10/17 by Bousquet, Olivier, Klochkov, Yegor, Zhivotovskiy, Nikita · 5 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR)
13. A Theory of Universal Learning
    2020/11/09 by Bousquet, Olivier, Hanneke, Steve, Moran, Shay +2 · 5 citations
    #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
14. AdaGAN: Boosting Generative Models
    2017/01/09 by Ilya Tolstikhin, Sylvain Gelly, Tolstikhin, Ilya +7 · 1 voice · 1 citation
    Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.LG #stat.ML
15. The Optimal Approximation Factor in Density Estimation
    2019/02/10 by Olivier Bousquet, Bousquet, Olivier, Daniel M. Kane +3 · 3 citations
    Computer Science · #Computability, Logic, AI Algorithms #Computational Complexity (cs.CC) #FOS: Computer and information sciences #FOS: Mathematics #Imbalanced Data Classification Techniques #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Probability (math.PR)
16. Compositional Semantic Parsing with Large Language Models
    2022/09/29 by Drozdov, Andrew, Schärli, Nathanael, Akyürek, Ekin +5 · 3 citations
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences
17. Proper Learning, Helly Number, and an Optimal SVM Bound
    2020/05/24 by Olivier Bousquet, Bousquet, Olivier, Steve Hanneke +5 · 3 citations
    Computer Science · #Machine Learning and Algorithms #Domain Adaptation and Few-Shot Learning #Complexity and Algorithms in Graphs
18. Monotone Learning
    2022/02/10 by Olivier Bousquet, Bousquet, Olivier, Amit Daniely +9 · 2 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification #Statistics Theory (math.ST)
19. Fast classification rates without standard margin assumptions
    2019/10/28 by Bousquet, Olivier, Zhivotovskiy, Nikita · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
20. Statistically Near-Optimal Hypothesis Selection
    2021/08/17 by Bousquet, Olivier, Braverman, Mark, Efremenko, Klim +2 · 1 citation
    #Artificial Intelligence (cs.AI) #Computational Complexity (cs.CC) #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Optimization and Control (math.OC)