Jean-Yves Audibert

6.2k total citations
36 papers, 2.3k citations indexed

About

Jean-Yves Audibert is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Jean-Yves Audibert has authored 36 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 17 papers in Artificial Intelligence and 8 papers in Management Science and Operations Research. Recurrent topics in Jean-Yves Audibert's work include Image Retrieval and Classification Techniques (10 papers), Machine Learning and Algorithms (9 papers) and Advanced Image and Video Retrieval Techniques (9 papers). Jean-Yves Audibert is often cited by papers focused on Image Retrieval and Classification Techniques (10 papers), Machine Learning and Algorithms (9 papers) and Advanced Image and Video Retrieval Techniques (9 papers). Jean-Yves Audibert collaborates with scholars based in France, United States and Germany. Jean-Yves Audibert's co-authors include Jean Ponce, Hui Kong, Csaba Szepesvári, Rémi Munos, Francis Bach, Rodolphe Jenatton, Ivan Laptev, Josef Šivic, Matthias Hein and Mikel Rodríguez and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Jean-Yves Audibert

35 papers receiving 2.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jean-Yves Audibert France 19 1.3k 949 346 318 218 36 2.3k
Tianbao Yang United States 21 605 0.5× 1.3k 1.4× 84 0.2× 231 0.7× 327 1.5× 106 2.4k
Samuel Rota Bulò Italy 29 2.1k 1.7× 1.3k 1.4× 152 0.4× 69 0.2× 255 1.2× 79 3.3k
Hujun Yin United Kingdom 27 1.0k 0.8× 948 1.0× 76 0.2× 109 0.3× 87 0.4× 164 2.5k
François Fleuret Switzerland 29 3.2k 2.6× 1.5k 1.6× 146 0.4× 39 0.1× 106 0.5× 93 4.3k
H.A.P. Blom Netherlands 27 244 0.2× 2.5k 2.6× 224 0.6× 172 0.5× 65 0.3× 145 4.2k
F.H.F. Leung Hong Kong 30 442 0.4× 1.5k 1.6× 118 0.3× 154 0.5× 75 0.3× 195 3.6k
Jun Zhang China 22 620 0.5× 316 0.3× 111 0.3× 42 0.1× 82 0.4× 236 2.2k
Erik B. Sudderth United States 31 1.4k 1.1× 1.3k 1.3× 46 0.1× 34 0.1× 88 0.4× 75 2.9k
Mario Sznaier United States 28 869 0.7× 532 0.6× 81 0.2× 85 0.3× 234 1.1× 277 3.5k
Hadi Sadoghi Yazdi Iran 22 489 0.4× 885 0.9× 48 0.1× 64 0.2× 175 0.8× 184 2.0k

Countries citing papers authored by Jean-Yves Audibert

Since Specialization
Citations

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

Fields of papers citing papers by Jean-Yves Audibert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean-Yves Audibert. 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 Jean-Yves Audibert. The network helps show where Jean-Yves Audibert may publish in the future.

Co-authorship network of co-authors of Jean-Yves Audibert

This figure shows the co-authorship network connecting the top 25 collaborators of Jean-Yves Audibert. A scholar is included among the top collaborators of Jean-Yves Audibert 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 Jean-Yves Audibert. Jean-Yves Audibert 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.
Audibert, Jean-Yves, et al.. (2013). Robustness of stochastic bandit policies. Theoretical Computer Science. 519. 46–67. 1 indexed citations
2.
Audibert, Jean-Yves, Sébastien Bubeck, & Gábor Lugosi. (2013). Regret in Online Combinatorial Optimization. Mathematics of Operations Research. 39(1). 31–45. 66 indexed citations
3.
Audibert, Jean-Yves, Sébastien Bubeck, & Gábor Lugosi. (2011). Minimax Policies for Combinatorial Prediction Games. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
4.
Rodríguez, Mikel, Josef Šivic, Ivan Laptev, & Jean-Yves Audibert. (2011). Data-driven crowd analysis in videos. HAL (Le Centre pour la Communication Scientifique Directe). 1235–1242. 146 indexed citations
5.
Audibert, Jean-Yves & Olivier Catoni. (2010). Robust linear regression through PAC-Bayesian truncation. arXiv (Cornell University). 6 indexed citations
6.
Kong, Hui, Jean-Yves Audibert, & Jean Ponce. (2010). Detecting Abandoned Objects With a Moving Camera. IEEE Transactions on Image Processing. 19(8). 2201–2210. 43 indexed citations
7.
Kong, Hui, Jean-Yves Audibert, & Jean Ponce. (2010). General Road Detection From a Single Image. IEEE Transactions on Image Processing. 19(8). 2211–2220. 304 indexed citations
8.
Sahbi, Hichem, Jean-Yves Audibert, & Renaud Keriven. (2010). Context-Dependent Kernels for Object Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence. 33(4). 699–708. 32 indexed citations
9.
Kong, Hui, Jean-Yves Audibert, & Jean Ponce. (2009). Vanishing point detection for road detection. 2009 IEEE Conference on Computer Vision and Pattern Recognition. 96–103. 182 indexed citations
10.
Sahbi, Hichem, et al.. (2009). Social Network Kernels for Image Ranking and Retrieval Noyaux de Similarite pour les Reseaux Sociaux. 2 indexed citations
11.
Audibert, Jean-Yves, Rémi Munos, & Csaba Szepesvári. (2009). Exploration–exploitation tradeoff using variance estimates in multi-armed bandits. Theoretical Computer Science. 410(19). 1876–1902. 255 indexed citations
12.
Wang, Yizao, Jean-Yves Audibert, & Rémi Munos. (2008). Algorithms for Infinitely Many-Armed Bandits. Neural Information Processing Systems. 21. 1729–1736. 39 indexed citations
13.
Audibert, Jean-Yves, Rémi Munos, & Csaba Szepesvári. (2008). Variance estimates and exploration function in multi-armed bandit. 7 indexed citations
14.
Sahbi, Hichem, Jean-Yves Audibert, Jaonary Rabarisoa, & Renaud Keriven. (2008). Context-dependent kernel design for object matching and recognition. 8. 1–8. 14 indexed citations
15.
Audibert, Jean-Yves. (2007). Progressive mixture rules are deviation suboptimal. Neural Information Processing Systems. 20. 41–48. 19 indexed citations
16.
Audibert, Jean-Yves & Olivier Bousquet. (2007). Combining PAC-Bayesian and Generic Chaining Bounds. Journal of Machine Learning Research. 8(32). 863–889. 14 indexed citations
17.
Hein, Matthias, Jean-Yves Audibert, & Ulrike von Luxburg. (2007). Graph Laplacians and their Convergence on Random Neighborhood Graphs. Journal of Machine Learning Research. 8(48). 1325–1370. 102 indexed citations
18.
Audibert, Jean-Yves & Alexandre B. Tsybakov. (2007). Fast learning rates for plug-in classifiers. The Annals of Statistics. 35(2). 144 indexed citations
19.
Farahmand, Amir massoud, Csaba Szepesvári, & Jean-Yves Audibert. (2007). Manifold-adaptive dimension estimation. PolyPublie (École Polytechnique de Montréal). 265–272. 60 indexed citations
20.
Audibert, Jean-Yves & Olivier Bousquet. (2003). PAC-Bayesian Generic Chaining. MPG.PuRe (Max Planck Society). 16. 1125–1132. 4 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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