World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
82
Citations
146389
World Ranking
920
National Ranking
499

Overview

Léon Bottou is affiliated with Facebook in the United States and works primarily in the field of Computer Science. Their research focuses significantly on Artificial Intelligence, with contributions spanning subfields such as Computer Vision and Pattern Recognition, Management Science and Operations Research, Molecular Biology, and Literature and Literary Theory.

Their work centers around key topics including Machine Learning and Algorithms, Domain Adaptation and Few-Shot Learning, Neural Networks and Applications, Machine Learning and Data Classification, Advanced Neural Network Applications, Risk and Portfolio Optimization, and Stochastic Gradient Optimization Techniques.

Léon Bottou has authored several influential papers published over recent years. Selected recent papers include:

  • Poincaré maps for analyzing complex hierarchies in single-cell data, 2020, Nature Communications
  • The Effects of Regularization and Data Augmentation are Class Dependent, 2022, arXiv (Cornell University)
  • A Simple Convergence Proof of Adam and Adagrad, 2020, arXiv (Cornell University)
  • Linear unit-tests for invariance discovery, 2021, arXiv (Cornell University)
  • Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation, 2021, arXiv (Cornell University)

The scientist frequently publishes in venues such as arXiv (Cornell University), where they have contributed 17 publications, Nature Communications, Proceedings of the AAAI Conference on Artificial Intelligence, and Neural Computing and Applications.

Léon Bottou collaborates with several researchers consistently. Frequent co-authors include Jianyu Zhang, David Lopez-Paz, Agnieszka Słowik, and Randall Balestriero.

Best Publications

  • Gradient-based learning applied to document recognition

    Yann Lecun;Leon Bottou;Leon Bottou;Yoshua Bengio;Yoshua Bengio;Yoshua Bengio;Patrick Haffner;Patrick Haffner

  • Wasserstein Generative Adversarial Networks

    Martin Arjovsky;Soumith Chintala;Léon Bottou

  • Natural Language Processing (Almost) from Scratch

    Ronan Collobert;Jason Weston;Léon Bottou;Michael Karlen

  • Large-Scale Machine Learning with Stochastic Gradient Descent

    Léon Bottou

  • Efficient BackProp

    Yann LeCun;Léon Bottou;Genevieve B. Orr;Klaus-Robert Müller

  • SIGNATURE VERIFICATION USING A “SIAMESE” TIME DELAY NEURAL NETWORK

    Jane Bromley;James W. Bentz;James W. Bentz;Léon Bottou;Léon Bottou;Isabelle Guyon

  • Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks

    Maxime Oquab;Maxime Oquab;Leon Bottou;Ivan Laptev;Josef Sivic

  • Efficient BackProp

    Unknown

  • Optimization Methods for Large-Scale Machine Learning

    Léon Bottou;Frank E. Curtis;Jorge Nocedal

  • Stochastic Gradient Descent Tricks

    Léon Bottou

  • The Tradeoffs of Large Scale Learning

    Olivier Bousquet;Léon Bottou

  • Learning methods for generic object recognition with invariance to pose and lighting

    Y. LeCun;Fu Jie Huang;L. Bottou

  • Towards Principled Methods for Training Generative Adversarial Networks

    Martín Arjovsky;Léon Bottou

  • Object Recognition with Gradient-Based Learning

    Yann LeCun;Patrick Haffner;Léon Bottou;Yoshua Bengio

  • Is object localization for free? - Weakly-supervised learning with convolutional neural networks

    Maxime Oquab;Leon Bottou;Ivan Laptev;Josef Sivic

  • Comparison of classifier methods: a case study in handwritten digit recognition

    L. Bottou;C. Cortes;C. Cortes;J.S. Denker;J.S. Denker;H. Drucker;H. Drucker

  • Learning algorithms for classification: A comparison on handwritten digit recognition

    Yann Lecun;L.D. Jackel;Leon Bottou;Leon Bottou;Corinna Cortes;Corinna Cortes

  • Comparison of learning algorithms for handwritten digit recognition

    Yann Lecun;L.D. Jackel;Leon Bottou;Leon Bottou;A. Brunot

  • Fast Kernel Classifiers with Online and Active Learning

    Antoine Bordes;Seyda Ertekin;Jason Weston;Léon Bottou

  • Wasserstein GAN

    Martin Arjovsky;Soumith Chintala;Léon Bottou

  • Proceedings of the 26th International Conference on Neural Information Processing Systems

    C. J. C. Burges;L. Bottou;M. Welling;Z. Ghahramani

  • Invariant Risk Minimization

    Martin Arjovsky;Léon Bottou;Ishaan Gulrajani;David Lopez-Paz

Frequent Co-Authors

Yann LeCun
Yann LeCun Facebook (United States)
Patrick Haffner
Patrick Haffner Interactions Corporation
Patrice Y. Simard
Patrice Y. Simard Microsoft (United States)
Vladimir Vapnik
Vladimir Vapnik Princeton University
Yoshua Bengio
Yoshua Bengio University of Montreal
Olivier Chapelle
Olivier Chapelle Google (United States)
Jason Weston
Jason Weston Facebook (United States)
David Lopez-Paz
David Lopez-Paz Facebook AI Research (FAIR) in Paris
Antoine Bordes
Antoine Bordes Facebook (United States)
Kilian Q. Weinberger
Kilian Q. Weinberger Cornell University

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