Bottou, Leon

61 publications

ICLR 2025 MagicPIG: LSH Sampling for Efficient LLM Generation Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Leon Bottou, Zhihao Jia, Beidi Chen

ICLR 2025 Memory Mosaics Jianyu Zhang, Niklas Nolte, Ranajoy Sadhukhan, Beidi Chen, Leon Bottou

NeurIPS 2025 Memory Mosaics at Scale Jianyu Zhang, Leon Bottou

NeurIPSW 2024 MagicPIG: LSH Sampling for Efficient LLM Generation Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Leon Bottou, Zhihao Jia, Beidi Chen

ICCV 2023 Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need Vivien Cabannes, Leon Bottou, Yann Lecun, Randall Balestriero

NeurIPS 2023 Birth of a Transformer: A Memory Viewpoint Alberto Bietti, Vivien Cabannes, Diane Bouchacourt, Herve Jegou, Leon Bottou

ICML 2023 Learning Useful Representations for Shifting Tasks and Distributions Jianyu Zhang, Leon Bottou

ICML 2023 Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization Alexandre Rame, Kartik Ahuja, Jianyu Zhang, Matthieu Cord, Leon Bottou, David Lopez-Paz

AISTATS 2022 On Distributionally Robust Optimization and Data Rebalancing Agnieszka Słowik, Leon Bottou

TMLR 2022 A Simple Convergence Proof of Adam and AdaGrad Alexandre Défossez, Leon Bottou, Francis Bach, Nicolas Usunier

AAAI 2022 On the Relation Between Distributionally Robust Optimization and Data Curation (Student Abstract) Agnieszka Slowik, Léon Bottou, Sean B. Holden, Mateja Jamnik

NeurIPSW 2022 Pre-Train, Fine-Tune, Interpolate: A Three-Stage Strategy for Domain Generalization Alexandre Rame, Jianyu Zhang, Leon Bottou, David Lopez-Paz

ICML 2022 Rich Feature Construction for the Optimization-Generalization Dilemma Jianyu Zhang, David Lopez-Paz, Leon Bottou

NeurIPS 2022 The Effects of Regularization and Data Augmentation Are Class Dependent Randall Balestriero, Leon Bottou, Yann LeCun

JMLR 2020 AdaGrad Stepsizes: Sharp Convergence over Nonconvex Landscapes Rachel Ward, Xiaoxia Wu, Leon Bottou

ICLR 2020 Scaling Laws for the Principled Design, Initialization, and Preconditioning of ReLU Networks Aaron Defazio, Leon Bottou

ICLR 2020 Symplectic Recurrent Neural Networks Zhengdao Chen, Jianyu Zhang, Martin Arjovsky, Léon Bottou

ICML 2019 AdaGrad Stepsizes: Sharp Convergence over Nonconvex Landscapes Rachel Ward, Xiaoxia Wu, Leon Bottou

NeurIPS 2019 Cold Case: The Lost MNIST Digits Chhavi Yadav, Leon Bottou

ICML 2019 First-Order Adversarial Vulnerability of Neural Networks and Input Dimension Carl-Johann Simon-Gabriel, Yann Ollivier, Leon Bottou, Bernhard Schölkopf, David Lopez-Paz

NeurIPS 2019 On the Ineffectiveness of Variance Reduced Optimization for Deep Learning Aaron Defazio, Leon Bottou

JMLR 2018 An Efficient Distributed Learning Algorithm Based on Effective Local Functional Approximations Dhruv Mahajan, Nikunj Agrawal, S. Sathiya Keerthi, Sundararajan Sellamanickam, Leon Bottou

NeurIPS 2018 SING: Symbol-to-Instrument Neural Generator Alexandre Defossez, Neil Zeghidour, Nicolas Usunier, Leon Bottou, Francis Bach

CVPR 2017 Discovering Causal Signals in Images David Lopez-Paz, Robert Nishihara, Soumith Chintala, Bernhard Scholkopf, Leon Bottou

ICLR 2017 Towards Principled Methods for Training Generative Adversarial Networks Martín Arjovsky, Léon Bottou

ICML 2017 Wasserstein Generative Adversarial Networks Martin Arjovsky, Soumith Chintala, Léon Bottou

AISTATS 2016 No Regret Bound for Extreme Bandits Robert Nishihara, David Lopez-Paz, Léon Bottou

ICLR 2016 Unifying Distillation and Privileged Information David Lopez-Paz, Léon Bottou, Bernhard Schölkopf, Vladimir Vapnik

ICML 2015 A Lower Bound for the Optimization of Finite Sums Alekh Agarwal, Leon Bottou

CVPR 2015 Is Object Localization for Free? - Weakly-Supervised Learning with Convolutional Neural Networks Maxime Oquab, Leon Bottou, Ivan Laptev, Josef Sivic

MLJ 2014 From Machine Learning to Machine Reasoning - An Essay Léon Bottou

MLJ 2014 Introduction to the Special Issue on Learning Semantics Antoine Bordes, Léon Bottou, Ronan Collobert, Dan Roth, Jason Weston, Luke Zettlemoyer

CVPR 2014 Learning and Transferring Mid-Level Image Representations Using Convolutional Neural Networks Maxime Oquab, Leon Bottou, Ivan Laptev, Josef Sivic

JMLR 2013 Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising Léon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X. Charles, D. Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard, Ed Snelson

JMLR 2011 Natural Language Processing (Almost) from Scratch Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, Pavel Kuksa

JMLR 2010 Erratum: SGDQN Is Less Careful than Expected Antoine Bordes, Léon Bottou, Patrick Gallinari, Jonathan Chang, S. Alex Smith

AISTATS 2010 Guarantees for Approximate Incremental SVMs Nicolas Usunier, Antoine Bordes, Léon Bottou

ICML 2009 Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, Montreal, Quebec, Canada, June 14-18, 2009 Andrea Pohoreckyj Danyluk, Léon Bottou, Michael L. Littman

JMLR 2009 SGD-QN: Careful Quasi-Newton Stochastic Gradient Descent Antoine Bordes, Léon Bottou, Patrick Gallinari

ECML-PKDD 2008 Sequence Labelling SVMs Trained in One Pass Antoine Bordes, Nicolas Usunier, Léon Bottou

ICML 2007 Solving Multiclass Support Vector Machines with LaRank Antoine Bordes, Léon Bottou, Patrick Gallinari, Jason Weston

JMLR 2007 The Need for Open Source Software in Machine Learning Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert Williamson

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

ICML 2006 Inference with the Universum Jason Weston, Ronan Collobert, Fabian H. Sinz, Léon Bottou, Vladimir Vapnik

JMLR 2006 Large Scale Transductive SVMs Ronan Collobert, Fabian Sinz, Jason Weston, Léon Bottou

ICML 2006 Trading Convexity for Scalability Ronan Collobert, Fabian H. Sinz, Jason Weston, Léon Bottou

JMLR 2005 Fast Kernel Classifiers with Online and Active Learning Antoine Bordes, Seyda Ertekin, Jason Weston, Léon Bottou

AISTATS 2005 Online (and Offline) on an Even Tighter Budget Jason Weston, Antoine Bordes, Leon Bottou

ECML-PKDD 2005 The Huller: A Simple and Efficient Online SVM Antoine Bordes, Léon Bottou

NeurIPS 2004 Breaking SVM Complexity with Cross-Training Léon Bottou, Jason Weston, Gökhan H. Bakir

CVPR 2004 Learning Methods for Generic Object Recognition with Invariance to Pose and Lighting Yann LeCun, Fu Jie Huang, Léon Bottou

NeurIPS 2004 Parallel Support Vector Machines: The Cascade SVM Hans P. Graf, Eric Cosatto, Léon Bottou, Igor Dourdanovic, Vladimir Vapnik

NeurIPS 2003 Geometric Clustering Using the Information Bottleneck Method Susanne Still, William Bialek, Léon Bottou

NeurIPS 2003 Large Scale Online Learning Léon Bottou, Yann L. Cun

NeurIPS 2000 Vicinal Risk Minimization Olivier Chapelle, Jason Weston, Léon Bottou, Vladimir Vapnik

NeurIPS 1998 Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks Patrice Simard, Léon Bottou, Patrick Haffner, Yann LeCun

CVPR 1997 Global Training of Document Processing Systems Using Graph Transformer Networks Léon Bottou, Yoshua Bengio, Yann LeCun

NeurIPS 1994 Convergence Properties of the K-Means Algorithms Léon Bottou, Yoshua Bengio

NeCo 1993 Local Algorithms for Pattern Recognition and Dependencies Estimation Vladimir Vapnik, Léon Bottou

NeCo 1992 Local Learning Algorithms Léon Bottou, Vladimir Vapnik

NeurIPS 1990 A Framework for the Cooperation of Learning Algorithms Léon Bottou, Patrick Gallinari