Olivier Chapelle

23.3k total citations · 10 hit papers
89 papers, 14.1k citations indexed

About

Olivier Chapelle is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Olivier Chapelle has authored 89 papers receiving a total of 14.1k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Artificial Intelligence, 36 papers in Computer Vision and Pattern Recognition and 16 papers in Information Systems. Recurrent topics in Olivier Chapelle's work include Face and Expression Recognition (24 papers), Machine Learning and Algorithms (19 papers) and Neural Networks and Applications (18 papers). Olivier Chapelle is often cited by papers focused on Face and Expression Recognition (24 papers), Machine Learning and Algorithms (19 papers) and Neural Networks and Applications (18 papers). Olivier Chapelle collaborates with scholars based in United States, Germany and United Kingdom. Olivier Chapelle's co-authors include Vladimir Vapnik, Alexander Zien, Bernhard Schölkopf, Sayan Mukherjee, Olivier Bousquet, Patrick Haffner, Ya Zhang, Jason Weston, S. Sathiya Keerthi and Lihong Li and has published in prestigious journals such as Bioinformatics, Neural Computation and European Journal of Medicinal Chemistry.

In The Last Decade

Olivier Chapelle

89 papers receiving 13.2k citations

Hit Papers

Semi-Supervised Learning 1999 2026 2008 2017 2006 2002 1999 2000 2009 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Olivier Chapelle United States 45 7.7k 5.5k 2.1k 1.1k 1.0k 89 14.1k
John Langford United States 37 7.2k 0.9× 6.0k 1.1× 1.3k 0.6× 1.8k 1.6× 1.2k 1.1× 115 15.1k
Hongyuan Zha United States 57 6.2k 0.8× 4.1k 0.8× 3.3k 1.6× 1.4k 1.2× 1.1k 1.0× 325 13.3k
Sankar K. Pal India 58 6.9k 0.9× 5.9k 1.1× 2.0k 0.9× 1.1k 1.0× 1.6k 1.5× 332 16.5k
Arthur Asuncion United States 13 13.5k 1.7× 4.7k 0.8× 2.7k 1.3× 1.9k 1.7× 830 0.8× 19 17.4k
Krzysztof J. Cios United States 29 6.3k 0.8× 3.7k 0.7× 1.3k 0.6× 1.2k 1.1× 663 0.6× 128 14.8k
Thomas G. Dietterich United States 48 8.5k 1.1× 3.9k 0.7× 1.8k 0.8× 1.1k 1.0× 642 0.6× 167 15.3k
Joydeep Ghosh United States 48 6.9k 0.9× 3.7k 0.7× 1.7k 0.8× 1.6k 1.5× 556 0.5× 308 14.9k
Christopher J. C. Burges United States 27 9.5k 1.2× 7.4k 1.3× 2.1k 1.0× 2.7k 2.4× 950 0.9× 43 23.5k
Qinghua Hu China 68 8.7k 1.1× 9.3k 1.7× 4.0k 1.9× 1.1k 1.0× 1.5k 1.5× 431 23.1k
Kilian Q. Weinberger United States 54 8.3k 1.1× 8.4k 1.5× 1.2k 0.6× 1.3k 1.2× 407 0.4× 133 17.0k

Countries citing papers authored by Olivier Chapelle

Since Specialization
Citations

This map shows the geographic impact of Olivier Chapelle'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 Olivier Chapelle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olivier Chapelle more than expected).

Fields of papers citing papers by Olivier Chapelle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Olivier Chapelle. 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 Olivier Chapelle. The network helps show where Olivier Chapelle may publish in the future.

Co-authorship network of co-authors of Olivier Chapelle

This figure shows the co-authorship network connecting the top 25 collaborators of Olivier Chapelle. A scholar is included among the top collaborators of Olivier Chapelle 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 Olivier Chapelle. Olivier Chapelle 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.
Xu, Zhixiang, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, & Olivier Chapelle. (2014). Classifier cascades and trees for minimizing feature evaluation cost. Journal of Machine Learning Research. 15(1). 2113–2144. 40 indexed citations
2.
Chen, Minmin, et al.. (2012). Classifier Cascade for Minimizing Feature Evaluation Cost. International Conference on Artificial Intelligence and Statistics. 218–226. 34 indexed citations
3.
Dhillon, Paramveer S., S. Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, & Sundararajan Sellamanickam. (2012). Deterministic Annealing for Semi-Supervised Structured Output Learning. International Conference on Artificial Intelligence and Statistics. 22. 299–307. 5 indexed citations
4.
Chapelle, Olivier & Lihong Li. (2011). An Empirical Evaluation of Thompson Sampling. Neural Information Processing Systems. 24. 2249–2257. 492 indexed citations breakdown →
5.
Chapelle, Olivier, Vikas Sindhwani, & S. Sathiya Keerthi. (2008). Optimization Techniques for Semi-Supervised Support Vector Machines. Journal of Machine Learning Research. 9(7). 203–233. 302 indexed citations
6.
Weinberger, Kilian Q. & Olivier Chapelle. (2008). Large Margin Taxonomy Embedding for Document Categorization. Neural Information Processing Systems. 21. 1737–1744. 39 indexed citations
7.
Weinberger, Kilian Q. & Olivier Chapelle. (2008). Large margin taxonomy embedding with an application to document categorization. neural information processing systems. 1737–1744. 11 indexed citations
8.
Chapelle, Olivier, Joshua Shulman, Choon Hui Teo, Quoc V. Le, & Alex Smola. (2008). Tighter Bounds for Structured Estimation. ANU Open Research (Australian National University). 21. 281–288. 33 indexed citations
9.
Bottou, Léon, Olivier Chapelle, Dennis DeCoste, & Jason Weston. (2007). Large-Scale Kernel Machines (Neural Information Processing). The MIT Press eBooks. 10 indexed citations
10.
Zheng, Zhaohui, Hongyuan Zha, Tong Zhang, et al.. (2007). A General Boosting Method and its Application to Learning Ranking Functions for Web Search. Journal of Bioresource Management. 20. 1697–1704. 129 indexed citations
11.
Chapelle, Olivier. (2005). Some thoughts about Gaussian Processes. MPG.PuRe (Max Planck Society). 1 indexed citations
12.
Chapelle, Olivier, et al.. (2005). Semi-Supervised Classification by Low Density Separation. Max Planck Institute for Plasma Physics. 57–64. 493 indexed citations breakdown →
13.
Chapelle, Olivier. (2005). Active Learning for Parzen Window Classifier. Max Planck Institute for Plasma Physics. 49–56. 22 indexed citations
14.
Chapelle, Olivier, Bernhard Schölkopf, & Jason Weston. (2003). Semi-Supervised Learning through Principal Directions Estimation. International Conference on Machine Learning. 14(11). 1–7. 2 indexed citations
15.
Chapelle, Olivier, Jason Weston, & Bernhard Schölkopf. (2002). Cluster Kernels for Semi-Supervised Learning. MPG.PuRe (Max Planck Society). 15. 601–608. 319 indexed citations
16.
Chapelle, Olivier & Bernhard Schölkopf. (2001). Incorporating invariances in nonlinear Support Vector Machines. MPG.PuRe (Max Planck Society). 609–616. 13 indexed citations
17.
Weston, Jason, et al.. (2001). KDD Cup 2001 data analysis: prediction of molecular bioactivity for drug Design-Binding to Thrombin. MPG.PuRe (Max Planck Society). 9 indexed citations
18.
Weston, Jason, Sayan Mukherjee, Olivier Chapelle, et al.. (2000). Feature Selection for SVMs. UCL Discovery (University College London). 13. 668–674. 692 indexed citations breakdown →
19.
Chapelle, Olivier, et al.. (1999). SVMs for Histogram Based Image Classification. MPG.PuRe (Max Planck Society). 132 indexed citations
20.
Chapelle, Olivier & Vladimir Vapnik. (1999). Model Selection for Support Vector Machines. MPG.PuRe (Max Planck Society). 12. 230–236. 237 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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