Levente Kocsis

3.7k total citations
24 papers, 373 citations indexed

About

Levente Kocsis is a scholar working on Artificial Intelligence, Management Science and Operations Research and Information Systems. According to data from OpenAlex, Levente Kocsis has authored 24 papers receiving a total of 373 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 10 papers in Management Science and Operations Research and 9 papers in Information Systems. Recurrent topics in Levente Kocsis's work include Recommender Systems and Techniques (9 papers), Advanced Bandit Algorithms Research (8 papers) and Reinforcement Learning in Robotics (4 papers). Levente Kocsis is often cited by papers focused on Recommender Systems and Techniques (9 papers), Advanced Bandit Algorithms Research (8 papers) and Reinforcement Learning in Robotics (4 papers). Levente Kocsis collaborates with scholars based in Hungary, Canada and Japan. Levente Kocsis's co-authors include Csaba Szepesvári, András György, Jan Willemson, András A. Benczúr, Róbert Pálovics, David Silver, Sylvain Gelly, Olivier Teytaud, Marc Schoenauer and Michèle Sébag and has published in prestigious journals such as Communications of the ACM, Machine Learning and Perception.

In The Last Decade

Levente Kocsis

24 papers receiving 350 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Levente Kocsis Hungary	9	218	81	77	67	53	24	373
Branislav Bošanský Czechia	14	188 0.9×	106 1.3×	106 1.4×	185 2.8×	35 0.7×	47	485
Y. Ding China	6	218 1.0×	133 1.6×	44 0.6×	77 1.1×	38 0.7×	13	427
James Pita United States	11	103 0.5×	103 1.3×	130 1.7×	145 2.2×	38 0.7×	19	630
Bikramjit Banerjee United States	11	370 1.7×	21 0.3×	101 1.3×	96 1.4×	26 0.5×	44	500
Vahida Attar India	12	247 1.1×	96 1.2×	108 1.4×	120 1.8×	25 0.5×	51	556
Xiaoyu Sean Lu China	12	202 0.9×	76 0.9×	28 0.4×	42 0.6×	6 0.1×	25	471
Eric Shieh United States	8	62 0.3×	41 0.5×	70 0.9×	105 1.6×	14 0.3×	16	339
Enrique Muñoz de Cote Mexico	13	201 0.9×	30 0.4×	170 2.2×	112 1.7×	15 0.3×	39	440
Maayan Roth United States	7	195 0.9×	59 0.7×	64 0.8×	94 1.4×	6 0.1×	7	315
Dharmveer Singh Rajpoot India	9	343 1.6×	144 1.8×	26 0.3×	48 0.7×	11 0.2×	23	459

Countries citing papers authored by Levente Kocsis

Since Specialization

Citations

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

Fields of papers citing papers by Levente Kocsis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Levente Kocsis

This figure shows the co-authorship network connecting the top 25 collaborators of Levente Kocsis. A scholar is included among the top collaborators of Levente Kocsis 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 Levente Kocsis. Levente Kocsis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Kocsis, Levente, et al.. (2021). Online convex combination of ranking models. User Modeling and User-Adapted Interaction. 32(4). 649–683. 2 indexed citations

Kocsis, Levente, et al.. (2019). Online ranking combination. 12–19. 1 indexed citations

Kocsis, Levente, et al.. (2018). Credit-to-GDP gap calculation using multivariate HP filter. Econstor (Econstor). 3 indexed citations

Pálovics, Róbert, et al.. (2017). Alpenglow: Open source recommender framework with time-Aware learning and evaluation. SZTAKI Publication Repository (Hungarian Academy of Sciences). 3 indexed citations

Pálovics, Róbert, et al.. (2017). Online ranking prediction in non-stationary environments. SZTAKI Publication Repository (Hungarian Academy of Sciences). 28–34. 3 indexed citations

Pálovics, Róbert, et al.. (2016). Location-aware online learning for top-k recommendation. Pervasive and Mobile Computing. 38. 490–504. 14 indexed citations

Hegedűs, István, et al.. (2016). Robust Decentralized Low-Rank Matrix Decomposition. ACM Transactions on Intelligent Systems and Technology. 7(4). 1–24. 18 indexed citations

Pálovics, Róbert, et al.. (2015). Location-aware online learning for top-k hashtag recommendation. Conference on Recommender Systems. 36–39. 4 indexed citations

Pálovics, Róbert, et al.. (2015). Solving RecSys Challenge 2015 by Linear Models, Gradient Boosted Trees and Metric Optimization. 1–4. 3 indexed citations

10.

Hegedűs, István, Márk Jelasity, Levente Kocsis, & András A. Benczúr. (2014). Fully distributed robust singular value decomposition. SZTE Publicatio Repozitórium (University of Szeged). 1–9. 5 indexed citations

11.

Pálovics, Róbert, et al.. (2014). RecSys Challenge 2014. 13–18. 1 indexed citations

12.

Kocsis, Levente, et al.. (2013). BoostingTree: parallel selection of weak learners in boosting, with application to ranking. Machine Learning. 93(2-3). 293–320. 3 indexed citations

13.

Gelly, Sylvain, Levente Kocsis, Marc Schoenauer, et al.. (2012). The grand challenge of computer Go. Communications of the ACM. 55(3). 106–113. 82 indexed citations

14.

Kocsis, Levente & András György. (2010). Fraud Detection by Generating Positive Samples for Classification from Unlabeled Data. SZTAKI Publication Repository (Hungarian Academy of Sciences). 2 indexed citations

15.

Kocsis, Levente, et al.. (2008). Transpositions and move groups in Monte Carlo tree search. 389–395. 41 indexed citations

16.

György, András, et al.. (2007). Continuous time associative bandit problems. SZTAKI Publication Repository (Hungarian Academy of Sciences). 830–835. 14 indexed citations

17.

Kocsis, Levente, Csaba Szepesvári, & Jan Willemson. (2006). Improved Monte-Carlo Search. 63 indexed citations

18.

Kocsis, Levente & Csaba Szepesvári. (2006). Universal parameter optimisation in games based on SPSA. Machine Learning. 63(3). 249–286. 14 indexed citations

19.

Kocsis, Levente, et al.. (2004). Visuo-tactile cortical network defined on graph-theoretical ground. Perception. 33. 0–0. 1 indexed citations

20.

Kocsis, Levente, H.J. van den Herik, & J.W.H.M. Uiterwijk. (2003). TWO LEARNING ALGORITHMS FOR FORWARD PRUNING. ICGA Journal. 26(3). 165–181. 1 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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