Léon Bottou
- Computer Vision and Pattern Recognition top 0.01%
- Advanced Data Compression Techniques 9
- Face and Expression Recognition 7
- Artificial Intelligence top 0.01%
- Neural Networks and Applications 24
- Machine Learning and Algorithms 21
- Stochastic Gradient Optimization Techniques 9
- Domain Adaptation and Few-Shot Learning 7
- Machine Learning and Data Classification 7
- Algorithms and Data Compression 6
- Media Technology top 0.02%
- Signal Processing top 0.05%
- Computational Mathematics top 0.5%
Léon Bottou
82 papers receiving 51.4k citations
Hit Papers
Peers
Comparison fields: 5 of 230
- Computer Vision and Pattern Recognition 21.9k
- Artificial Intelligence 23.9k
- Media Technology 3.8k
- Signal Processing 3.9k
- Computational Mathematics 155
Countries citing papers authored by Léon Bottou
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
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
The 25 scholars most cited alongside Léon Bottou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Symplectic Recurrent Neural Networks | 2020 | 14 |
| 2 | Cold Case: The Lost MNIST Digits | 2019 | 11 |
| 3 | AdaGrad stepsizes: Sharp convergence over nonconvex landscapes, from any initialization | 2018 | 24 |
| 4 | AdaGrad stepsizes: Sharp convergence over nonconvex landscapes | 2018 | 28 |
| 5 | Wasserstein Generative Adversarial Networksbreakdown → | 2017 | 2782 |
| 6 | 2012 | 57 | |
| 7 | Proceedings of the 26th Annual International Conference on Machine Learningbreakdown → | 2009 | 583 |
| 8 | 2006 | 254 | |
| 9 | Large Scale Transductive SVMs | 2006 | 355 |
| 10 | Advances in Neural Information Processing Systems 17: Proceedings of the 2004 Conference (Bradford Books) | 2005 | 4 |
| 11 | Geometric Clustering Using the Information Bottleneck Method | 2003 | 17 |
| 12 | DjVu document browsing with on-demand loading and rendering of image components | 2001 | 1 |
| 13 | Vicinal Risk Minimization | 2000 | 120 |
| 14 | Efficient BackPropbreakdown → | 1998 | 951 |
| 15 | Gradient-based learning applied to document recognitionbreakdown → | 1998 | 34531 |
| 16 | Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural Networks | 1998 | 81 |
| 17 | Convergence Properties of the K-Means Algorithms | 1994 | 255 |
| 18 | Structural Risk Minimization for Character Recognition | 1991 | 59 |
| 19 | A Framework for the Cooperation of Learning Algorithms | 1990 | 29 |
| 20 | Comparison of neural and conventional classifiers on a speech recognition problem | 1989 | 5 |
About Léon Bottou
Léon Bottou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 84 papers that have together received 53.8k indexed citations. Recurring topics across this work include Neural Networks and Applications (24 papers), Machine Learning and Algorithms (21 papers), Advanced Data Compression Techniques (9 papers), Stochastic Gradient Optimization Techniques (9 papers), Face and Expression Recognition (7 papers), Domain Adaptation and Few-Shot Learning (7 papers), Machine Learning and Data Classification (7 papers) and Algorithms and Data Compression (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (21.9k citations), Artificial Intelligence (23.9k citations) and Media Technology (3.8k citations). Léon Bottou has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Yoshua Bengio, Yann LeCun, Patrick Haffner, Martín Arjovsky, Soumith Chintala, Daphne Koller, Dale Schuurmans, Josef Šivic, Ivan Laptev and Maxime Oquab. Their work appears in journals such as Journal of Machine Learning Research, Machine Learning, Neural Computation, IEEE Transactions on Circuits and Systems for Video Technology and Journal of Proteome Research.
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.