Jean-Yves Audibert

6.2k citations
36 papers · 2.3k indexed · h-index 19
Topics
Image Retrieval and Classification Techniques (10 papers)Machine Learning and Algorithms (9 papers)Advanced Image and Video Retrieval Techniques (9 papers)

In The Last Decade

Jean-Yves Audibert

35 papers receiving 2.2k citations

Peers

Jean-Yves Audibert
Comparison fields: 5 of 120
  • Computer Vision and Pattern Recognition 1.3k
  • Artificial Intelligence 949
  • Automotive Engineering 346
  • Management Science and Operations Research 318
  • Computational Mechanics 218
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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
#WorkIndexed citations
1 1
2
Minimax Policies for Combinatorial Prediction Games
1
3 146
4
Robust linear regression through PAC-Bayesian truncation
6
5 43
6 304
7 32
8 182
9 255
10
Social Network Kernels for Image Ranking and Retrieval Noyaux de Similarite pour les Reseaux Sociaux
2
11
Algorithms for Infinitely Many-Armed Bandits
39
12
Variance estimates and exploration function in multi-armed bandit
7
13 14
14 1
15
Combining PAC-Bayesian and Generic Chaining Bounds
14
16
Progressive mixture rules are deviation suboptimal
19
17 102
18 60
19 144
20
PAC-Bayesian Generic Chaining
4

About Jean-Yves Audibert

Jean-Yves Audibert is a scholar working on Computer Vision and Pattern Recognition, Statistics and Probability and Management Science and Operations Research, having authored 36 papers that have together received 2.3k indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (10 papers), Machine Learning and Algorithms (9 papers) and Advanced Image and Video Retrieval Techniques (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.3k citations), Artificial Intelligence (949 citations) and Automotive Engineering (346 citations). Jean-Yves Audibert has collaborated with scholars based in France, United States and Germany. Frequent co-authors include Jean Ponce, Hui Kong, Csaba Szepesvári, Rémi Munos, Francis Bach, Rodolphe Jenatton, Ivan Laptev, Mikel Rodríguez, Matthias Hein and Josef Šivic. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

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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