Léon Bottou

116.4k total citations · 10 hit papers
84 papers, 53.8k citations indexed

About

Léon Bottou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Léon Bottou has authored 84 papers receiving a total of 53.8k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Artificial Intelligence, 32 papers in Computer Vision and Pattern Recognition and 12 papers in Signal Processing. Recurrent topics in Léon Bottou's work include Neural Networks and Applications (24 papers), Machine Learning and Algorithms (21 papers) and Advanced Data Compression Techniques (9 papers). Léon Bottou is often cited by papers focused on Neural Networks and Applications (24 papers), Machine Learning and Algorithms (21 papers) and Advanced Data Compression Techniques (9 papers). Léon Bottou collaborates with scholars based in United States, Germany and France. Léon Bottou's co-authors include Yoshua Bengio, Yann LeCun, Patrick Haffner, Martín Arjovsky, Soumith Chintala, Dale Schuurmans, Daphne Koller, Maxime Oquab, Josef Šivic and Ivan Laptev and has published in prestigious journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and Proceedings of the IEEE.

In The Last Decade

Léon Bottou

82 papers receiving 51.4k citations

Hit Papers

Gradient-based learning applied to document recognition 1993 2026 2004 2015 1998 2008 2017 2014 1993 10.0k 20.0k 30.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Léon Bottou United States 40 23.9k 21.9k 5.5k 3.9k 3.8k 84 53.8k
Ruslan Salakhutdinov United States 55 26.1k 1.1× 19.9k 0.9× 3.9k 0.7× 5.4k 1.4× 2.5k 0.7× 147 56.5k
Corinna Cortes United States 33 20.7k 0.9× 13.5k 0.6× 4.3k 0.8× 4.5k 1.1× 2.9k 0.8× 76 58.8k
Chih‐Jen Lin Taiwan 54 18.7k 0.8× 16.3k 0.7× 3.8k 0.7× 4.9k 1.3× 3.7k 1.0× 145 51.7k
Patrick Haffner United States 20 16.1k 0.7× 15.0k 0.7× 4.6k 0.8× 2.7k 0.7× 2.8k 0.7× 57 37.5k
Karen Simonyan United States 23 21.1k 0.9× 34.0k 1.6× 4.6k 0.8× 3.3k 0.8× 5.6k 1.5× 49 63.3k
Alex Krizhevsky Canada 7 24.9k 1.0× 31.3k 1.4× 5.7k 1.0× 5.1k 1.3× 5.3k 1.4× 7 70.5k
Vincent Vanhoucke United States 19 23.2k 1.0× 30.8k 1.4× 4.1k 0.7× 6.3k 1.6× 4.8k 1.3× 37 62.8k
Andrew Y. Ng United States 88 39.6k 1.7× 21.0k 1.0× 2.4k 0.4× 5.4k 1.4× 3.0k 0.8× 208 68.8k
Qiang Yang Hong Kong 98 32.1k 1.3× 13.7k 0.6× 6.2k 1.1× 4.7k 1.2× 2.1k 0.6× 860 62.9k
Yangqing Jia United States 24 14.2k 0.6× 27.0k 1.2× 3.1k 0.6× 2.6k 0.7× 4.4k 1.2× 39 44.1k

Countries citing papers authored by Léon Bottou

Since Specialization
Citations

This map shows the geographic impact of Léon Bottou's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Léon Bottou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Léon Bottou more than expected).

Fields of papers citing papers by Léon Bottou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Léon Bottou. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Léon Bottou. The network helps show where Léon Bottou may publish in the future.

Co-authorship network of co-authors of Léon Bottou

This figure shows the co-authorship network connecting the top 25 collaborators of Léon Bottou. A scholar is included among the top collaborators of Léon Bottou based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Léon Bottou. Léon Bottou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chen, Zhengdao, Jianyu Zhang, Martín Arjovsky, & Léon Bottou. (2020). Symplectic Recurrent Neural Networks. International Conference on Learning Representations. 14 indexed citations
2.
Bottou, Léon, et al.. (2019). Cold Case: The Lost MNIST Digits. arXiv (Cornell University). 32. 13443–13452. 11 indexed citations
3.
Sagun, Levent, Utku Evci, V. Uğur Güney, Yann Dauphin, & Léon Bottou. (2018). Empirical Analysis of the Hessian of Over-Parametrized Neural Networks. International Conference on Learning Representations. 8 indexed citations
4.
Ward, Rachel, Xiaoxia Wu, & Léon Bottou. (2018). AdaGrad stepsizes: Sharp convergence over nonconvex landscapes. Journal of Machine Learning Research. 21(219). 1–30. 28 indexed citations
5.
Ward, Rachel, Xiaoxia Wu, & Léon Bottou. (2018). AdaGrad stepsizes: Sharp convergence over nonconvex landscapes, from any initialization. arXiv (Cornell University). 24 indexed citations
6.
Arjovsky, Martín, Soumith Chintala, & Léon Bottou. (2017). Wasserstein Generative Adversarial Networks. International Conference on Machine Learning. 214–223. 2782 indexed citations breakdown →
7.
Bottou, Léon, Jonas Peters, Joaquin Quiñonero-Candela, et al.. (2013). Counterfactual reasoning and learning systems: the example of computational advertising. Journal of Machine Learning Research. 14(1). 3207–3260. 208 indexed citations
8.
Bottou, Léon, Jonas Peters, Joaquin Quiñonero-Candela, et al.. (2012). Counterfactual Reasoning and Learning Systems. Journal of Machine Learning Research. 57 indexed citations
9.
Danyluk, Andrea, Léon Bottou, & Michael L. Littman. (2009). Proceedings of the 26th Annual International Conference on Machine Learning. International Conference on Machine Learning. 583 indexed citations breakdown →
10.
Bottou, Léon, Olivier Chapelle, Dennis DeCoste, & Jason Weston. (2007). Large-Scale Kernel Machines (Neural Information Processing). The MIT Press eBooks. 10 indexed citations
11.
Collobert, Ronan, Fabian H. Sinz, Jason Weston, & Léon Bottou. (2006). Large Scale Transductive SVMs. Journal of Machine Learning Research. 7(62). 1687–1712. 355 indexed citations
12.
Saul, Lawrence K., Yair Weiss, & Léon Bottou. (2005). Advances in Neural Information Processing Systems 17: Proceedings of the 2004 Conference (Bradford Books). The MIT Press eBooks. 4 indexed citations
13.
Still, Susanne, William Bialek, & Léon Bottou. (2003). Geometric Clustering Using the Information Bottleneck Method. neural information processing systems. 16. 1165–1172. 17 indexed citations
14.
Bottou, Léon, et al.. (2001). DjVu document browsing with on-demand loading and rendering of image components. 1 indexed citations
15.
LeCun, Yann, Léon Bottou, Genevieve Orr, & Klaus‐Robert Müller. (1998). Efficient BackProp. Neural Information Processing Systems. 9–50. 951 indexed citations breakdown →
16.
Simard, Patrice, Léon Bottou, Patrick Haffner, & Yann LeCun. (1998). Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks. neural information processing systems. 11. 571–577. 81 indexed citations
17.
LeCun, Yann, Léon Bottou, Yoshua Bengio, & Patrick Haffner. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE. 86(11). 2278–2324. 34531 indexed citations breakdown →
18.
Guyon, Isabelle, Vladimir Vapnik, Bernhard E. Boser, Léon Bottou, & Sara A. Solla. (1991). Structural Risk Minimization for Character Recognition. Neural Information Processing Systems. 4. 471–479. 59 indexed citations
19.
Bottou, Léon & Patrick Gallinari. (1990). A Framework for the Cooperation of Learning Algorithms. Neural Information Processing Systems. 3. 781–788. 29 indexed citations
20.
Bottou, Léon, et al.. (1989). Comparison of neural and conventional classifiers on a speech recognition problem. 86–89. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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