Ata Kaban

University of Birmingham

H-index: 29

Europe-United Kingdom

Ata Kaban, With an exceptional h-index of 29 and a recent h-index of 18 (since 2020), a distinguished researcher at University of Birmingham,

His recent articles reflect a diverse array of research interests and contributions to the field:

Structure discovery in PAC-learning by random projections

Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms

PAC-learning with approximate predictors

Optimisation and Learning With Randomly Compressed Gradient Updates

The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification

Heterogeneous sets in dimensionality reduction and ensemble learning

Noise-efficient Learning of Differentially Private Partitioning Machine Ensembles

Random projection through the lens of data complexity indicators

Title	Journal	Author(s)	Publication Date
Structure discovery in PAC-learning by random projections	Machine Learning	Ata Kabán Henry Reeve	2024/3/26
Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms		Sijia Zhou Yunwen Lei Ata Kaban	2024/2
PAC-learning with approximate predictors	Machine Learning	Andrew J. Turner Ata Kaban	2023/2
Optimisation and Learning With Randomly Compressed Gradient Updates	Neural Computation	Zhanliang Huang Yunwen Lei Ata Kabán	2023/6/12
The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification	Statistics and Computing	Efstratios Palias Ata Kabán	2023/6
Heterogeneous sets in dimensionality reduction and ensemble learning	Machine Learning	Henry WJ Reeve Ata Kabán Jakramate Bootkrajang	2022/10/28
Noise-efficient Learning of Differentially Private Partitioning Machine Ensembles		Zhanliang Huang Yunwen Lei Ata Kabán	2022
Random projection through the lens of data complexity indicators		Yamonporn Thummanusarn Ata Kabán	2021/12/7
Statistical optimality conditions for compressive ensembles	arXiv preprint arXiv:2106.01092	Henry WJ Reeve Ata Kaban	2021/6/2
Structure from Randomness in Halfspace Learning with the Zero-One Loss	Journal of Artificial Intelligence Research	Ata Kabán Robert J Durrant	2020/11/9
Sufficient ensemble size for random matrix theory-based handling of singular covariance matrices	Analysis and Applications	Ata Kabán	2020/9/17