Tanguy Urvoy

440 citations
14 papers · 157 indexed · h-index 5

Tanguy Urvoy

14 papers receiving 145 citations

Peers

Tanguy Urvoy
Comparison fields: 5 of 21
  • Information Systems 86
  • Artificial Intelligence 106
  • Management Science and Operations Research 40
  • Signal Processing 18
  • Computer Networks and Communications 24
Replace Diego Ceccarelli with:
Diego Ceccarelli Italy
Guglielmo Faggioli Italy
Mehdi Allahyari United States
Negar Arabzadeh Canada
Faegheh Hasibi Netherlands
Deqing Yang China
Yiheng Shu China
Francesco Corcoglioniti Italy
Jinze Bai China
Joanna Biega Germany
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Citations per year

Countries citing papers authored by Tanguy Urvoy

Since Specialization
Citations

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

Fields of papers citing papers by Tanguy Urvoy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 12 scholars most cited alongside Tanguy Urvoy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tanguy Urvoy Line = papers co-authored together Tanguy Urvoy links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 20231
2 20221
3 20211
4
Scaling up budgeted reinforcement learning.
20192
5
Random Forest for the Contextual Bandit Problem
201613
6
Bandit Structured Prediction for Learning from Partial Feedback in Statistical Machine Translation
20164
7
Generic Exploration and K-armed Voting Bandits
201321
8
Generic Exploration and K-armed Voting Bandits (extended version)
20131
9 20132
10
A stochastic bandit algorithm for scratch games
20123
11 20102
12
Detecting fake content with relative entropy scoring
200815
13 200862
14
Tracking Web Spam with Hidden Style Similarity
200629

About Tanguy Urvoy

Tanguy Urvoy is a scholar working on Management Science and Operations Research, Artificial Intelligence and Information Systems, having authored 14 papers that have together received 157 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (6 papers), Topic Modeling (5 papers), Spam and Phishing Detection (4 papers), Auction Theory and Applications (4 papers), Data Stream Mining Techniques (3 papers), Speech and dialogue systems (2 papers), Machine Learning and Algorithms (2 papers) and Misinformation and Its Impacts (2 papers). The work is most often cited by research in Information Systems (86 citations), Artificial Intelligence (106 citations) and Management Science and Operations Research (40 citations). Tanguy Urvoy has collaborated with scholars based in France and Germany. Frequent co-authors include Thomas Lavergne, Fabrice Clérot, François Yvon, Raphaël Féraud, Lina M. Rojas Barahona, Artem Sokolov, Stefan Riezler, Fabrice Lefèvre, Edouard Leurent and Romain Laroche. Their work appears in journals such as Machine Learning, Language Resources and Evaluation and ACM Transactions on the Web.

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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