Ata Kabán

1.9k citations
84 papers · 1.1k · h-index 20

Impact in

    • Bayesian Methods and Mixture Models
    • Metaheuristic Optimization Algorithms Research
    • Machine Learning and Data Classification
    • Neural Networks and Applications
    • Topic Modeling

Papers in

Ata Kabán

80 papers receiving 992 citations

Peers

Ata Kabán
Comparison fields: 5 of 109
  • Artificial Intelligence 709
  • Signal Processing 198
  • Computational Mathematics 10
  • Computer Vision and Pattern Recognition 323
  • Statistics and Probability 87
Replace Michael Collins with:
Michael Collins United States
Choon Hui Teo United States
Hisashi Kashima Japan
Tibério S. Caetano Australia
Cédric Archambeau United Kingdom
Purushottam Kar India
Elżbieta Pękalska Netherlands
Ding Zhou United States
Christian Sohler Germany
Aleksander Mądry United States
Ata Kabán relative to Michael Collins United States Michael Collins's profile →
Citations per field
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Michael Collins · 1×
Citations per year

Countries citing papers authored by Ata Kabán

Since Specialization
Citations

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

Fields of papers citing papers by Ata Kabán

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ata Kabán, 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 Ata Kabán Line = papers co-authored together Ata Kabán links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003120
2
A Comprehensive Introduction to Label Noise
201457
3 200949
4 201541
5 201141
6 200738
7 200137
8 201434
9 201332
10 201032
11 200331
12 201427
13 200525
14
Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles
200324
15
New Bounds on Compressive Linear Least Squares Regression
201421
16 200821
17 201020
18 200720
19 200419
20 200219

About Ata Kabán

Ata Kabán is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Statistics and Probability and Signal Processing, having authored 84 papers that have together received 1.1k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (19 papers), Face and Expression Recognition (18 papers), Bayesian Methods and Mixture Models (16 papers), Machine Learning and Algorithms (14 papers), Statistical Methods and Inference (9 papers), Metaheuristic Optimization Algorithms Research (9 papers), Machine Learning and Data Classification (9 papers) and Blind Source Separation Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (709 citations), Signal Processing (198 citations), Computational Mathematics (10 citations), Computer Vision and Pattern Recognition (323 citations) and Statistics and Probability (87 citations). Ata Kabán has collaborated with scholars based in United Kingdom, New Zealand and Finland. Frequent co-authors include Mark Girolami, Robert J. Durrant, Jakramate Bootkrajang, Ella Bingham, Benoît Frénay‬, Jianyong Sun, Peter Tiňo, Jonathan M. Garibaldi, Mikael Fortelius and Somak Raychaudhury. Their work appears in journals such as Machine Learning, Neurocomputing, Data Mining and Knowledge Discovery, Pattern Recognition Letters and Statistics and Computing.

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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