Gábor Bartók

835 citations
19 papers · 392 · h-index 10

Impact in

Papers in

Gábor Bartók

18 papers receiving 379 citations

Peers

Gábor Bartók
Comparison fields: 5 of 51
  • Transportation 135
  • Management Science and Operations Research 169
  • Automotive Engineering 110
  • Computer Science Applications 45
  • Artificial Intelligence 162
Replace Karthik Abinav Sankararaman with:
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Citations per year

Countries citing papers authored by Gábor Bartók

Since Specialization
Citations

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

Fields of papers citing papers by Gábor Bartók

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Gábor Bartók, 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 Gábor Bartók Line = papers co-authored together Gábor Bartók links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 2015172
2 201445
3 201443
4 201321
5 201218
6 201218
7
Minimax Regret of Finite Partial-Monitoring Games in Stochastic Environments
201117
8
A near-optimal algorithm for finite partial-monitoring games against adversarial opponents
201317
9
Online Learning with Costly Features and Labels
201311
10 20109
11
On Actively Teaching the Crowd to Classify
20136
12 20224
13
Efficient Partial Monitoring with Prior Information
20144
14
Gumbel-Matrix Routing for Flexible Multi-task Learning
20193
15 20201
16 20081
17 20121
18 20091
19 20140

About Gábor Bartók

Gábor Bartók is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Computer Science Applications and Computational Theory and Mathematics, having authored 19 papers that have together received 392 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (11 papers), Advanced Bandit Algorithms Research (11 papers), Optimization and Search Problems (5 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Game Theory and Applications (2 papers), Reinforcement Learning in Robotics (2 papers), Algorithms and Data Compression (2 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Transportation (135 citations), Management Science and Operations Research (169 citations), Automotive Engineering (110 citations), Computer Science Applications (45 citations) and Artificial Intelligence (162 citations). Gábor Bartók has collaborated with scholars based in Switzerland, Canada and Hungary. Frequent co-authors include Adish Singla, Csaba Szepesvári, Andreas Krause, Dávid Pál, Gergely Neu, Ilija Bogunovic, Amin Karbasi, Andreas Krause, Alexander Rakhlin and Dean P. Foster. Their work appears in journals such as Theoretical Computer Science, Information and Computation, Pharmaceuticals, Mathematics of Operations Research and Lecture notes in computer science.

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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