H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 70 Citations 144,465 146 World Ranking 824 National Ranking 491

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of investigation include Artificial intelligence, Machine learning, Pattern recognition, Training set and Support vector machine. Léon Bottou regularly ties together related areas like Algorithm in his Artificial intelligence studies. Léon Bottou studies Pattern recognition, focusing on Handwriting recognition in particular.

His research integrates issues of Neocognitron, Vanishing gradient problem, Optical character recognition and Intelligent character recognition in his study of Handwriting recognition. In his research on the topic of Training set, Tag system is strongly related with Task. He has researched Support vector machine in several fields, including Scalability, Scalable algorithms and Data mining.

His most cited work include:

  • Gradient-based learning applied to document recognition (26443 citations)
  • Gradient-based learning applied to document recognition (26443 citations)
  • Natural Language Processing (Almost) from Scratch (5058 citations)

What are the main themes of his work throughout his whole career to date?

Léon Bottou mostly deals with Artificial intelligence, Machine learning, Pattern recognition, Algorithm and Support vector machine. His research on Artificial intelligence often connects related areas such as Computer vision. Many of his studies on Machine learning involve topics that are commonly interrelated, such as Training set.

Léon Bottou works in the field of Pattern recognition, focusing on Handwriting recognition in particular. In his study, Stochastic gradient descent is strongly linked to Mathematical optimization, which falls under the umbrella field of Algorithm. His Convolutional neural network study combines topics in areas such as Optical character recognition and Transformer.

He most often published in these fields:

  • Artificial intelligence (62.69%)
  • Machine learning (26.37%)
  • Pattern recognition (22.89%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (62.69%)
  • Artificial neural network (13.43%)
  • Theoretical computer science (7.96%)

In recent papers he was focusing on the following fields of study:

Léon Bottou mainly focuses on Artificial intelligence, Artificial neural network, Theoretical computer science, Deep learning and Applied mathematics. His Artificial intelligence study incorporates themes from Machine learning, Optimization problem and Pattern recognition. His work on Recurrent neural network as part of general Artificial neural network research is often related to Initialization, Hamiltonian mechanics and Dynamical systems theory, thus linking different fields of science.

The Theoretical computer science study combines topics in areas such as Embedding, Cluster analysis and Visualization. His study focuses on the intersection of Deep learning and fields such as Spectrogram with connections in the field of Generator. His Applied mathematics research incorporates themes from Stochastic gradient descent, Parametric statistics and Lipschitz continuity.

Between 2017 and 2021, his most popular works were:

  • Optimization Methods for Large-Scale Machine Learning (1012 citations)
  • Invariant Risk Minimization (215 citations)
  • AdaGrad stepsizes: Sharp convergence over nonconvex landscapes, from any initialization (61 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

His scientific interests lie mostly in Artificial intelligence, Deep learning, Stochastic gradient descent, Lipschitz continuity and Artificial neural network. The study incorporates disciplines such as Optimization problem, Machine learning, Invariant and Pattern recognition in addition to Artificial intelligence. His Machine learning study focuses on Deep neural networks in particular.

His Deep learning research is multidisciplinary, relying on both Gradient descent and Normalization. His Stochastic gradient descent research is multidisciplinary, incorporating elements of Stationary point, Robustness and Applied mathematics. His work on Recurrent neural network as part of general Artificial neural network study is frequently connected to Hamiltonian mechanics, Dynamical systems theory and Symplectic integrator, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Gradient-based learning applied to document recognition

Yann Lecun;Leon Bottou;Leon Bottou;Yoshua Bengio;Yoshua Bengio;Yoshua Bengio;Patrick Haffner;Patrick Haffner.
Proceedings of the IEEE (1998)

30145 Citations

Wasserstein Generative Adversarial Networks

Martin Arjovsky;Soumith Chintala;Léon Bottou.
international conference on machine learning (2017)

7095 Citations

Natural Language Processing (Almost) from Scratch

Ronan Collobert;Jason Weston;Léon Bottou;Michael Karlen.
Journal of Machine Learning Research (2011)

5881 Citations

Large-Scale Machine Learning with Stochastic Gradient Descent

Léon Bottou.
COMPSTAT (2010)

4697 Citations

Wasserstein GAN

Martin Arjovsky;Soumith Chintala;Léon Bottou.
arXiv: Machine Learning (2017)

4145 Citations

Efficient BackProp

Yann LeCun;Léon Bottou;Genevieve B. Orr;Klaus-Robert Müller.
neural information processing systems (1998)

3747 Citations

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

Maxime Oquab;Maxime Oquab;Leon Bottou;Ivan Laptev;Josef Sivic.
computer vision and pattern recognition (2014)

2959 Citations

The Tradeoffs of Large Scale Learning

Olivier Bousquet;Léon Bottou.
neural information processing systems (2007)

1614 Citations

Stochastic Gradient Descent Tricks

Léon Bottou.
Neural Networks: Tricks of the Trade (2nd ed.) (2012)

1355 Citations

Optimization Methods for Large-Scale Machine Learning

Léon Bottou;Frank E. Curtis;Jorge Nocedal.
Siam Review (2018)

1337 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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