Róbert Busa‐Fekete

2.3k citations
41 papers · 1.3k indexed · h-index 18
Topics
Advanced Bandit Algorithms Research (10 papers)Machine Learning and Algorithms (7 papers)Speech Recognition and Synthesis (7 papers)

In The Last Decade

Róbert Busa‐Fekete

40 papers receiving 1.3k citations

Peers

Róbert Busa‐Fekete
Comparison fields: 5 of 144
  • Artificial Intelligence 474
  • Molecular Biology 317
  • Molecular Medicine 279
  • Genetics 275
  • Management Science and Operations Research 132
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Countries citing papers authored by Róbert Busa‐Fekete

Since Specialization
Citations

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

Fields of papers citing papers by Róbert Busa‐Fekete

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Róbert Busa‐Fekete. 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 Róbert Busa‐Fekete. The network helps show where Róbert Busa‐Fekete may publish in the future.

Co-authorship network of co-authors of Róbert Busa‐Fekete

This figure shows the co-authorship network connecting the top 25 collaborators of Róbert Busa‐Fekete. A scholar is included among the top collaborators of Róbert Busa‐Fekete 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 Róbert Busa‐Fekete. Róbert Busa‐Fekete 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
Identity testing for Mallows model
1
3
Private and Non-private Uniformity Testing for Ranking Data
1
4 2
5
Distributed Stochastic Optimization via Adaptive Stochastic Gradient Descent.
2
6
Ranking Distributions based on Noisy Sorting.
1
7
Multi-objective Bandits: Optimizing the Generalized Gini Index
6
8
Extreme F-measure maximization using sparse probability estimates
28
9
Online rank elicitation for Plackett-Luce: a dueling bandits approach
20
10 179
11 13
12
Gossip-based distributed stochastic bandit algorithms
22
13 253
14
MULTIBOOST: a multi-purpose boosting package
60
15
An apple-to-apple comparison of Learning-to-rank algorithms in terms of Normalized Discounted Cumulative Gain
10
16
Fast boosting using adversarial bandits
22
17
Accelerating AdaBoost using UCB
23
18 21
19 67
20 94

About Róbert Busa‐Fekete

Róbert Busa‐Fekete is a scholar working on Management Science and Operations Research, Artificial Intelligence and Signal Processing, having authored 41 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (10 papers), Machine Learning and Algorithms (7 papers) and Speech Recognition and Synthesis (7 papers). The work is most often cited by research in Molecular Medicine (279 citations), Artificial Intelligence (474 citations) and Health Information Management (66 citations). Róbert Busa‐Fekete has collaborated with scholars based in Hungary, United States and France. Frequent co-authors include Balázs Kégl, György Szarvas, Richárd Farkas, Csaba Pál, Viktória Lázár, Gergely Fekete, Balázs Papp, Gábor Gosztolya, László Tóth and Balázs Szappanos. Their work appears in journals such as Nature Communications, Antimicrobial Agents and Chemotherapy and Machine Learning.

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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