Kabán, Ata

28 publications

UAI 2025 Learning to Sample in Stochastic Optimization Sijia Zhou, Yunwen Lei, Ata Kaban

MLJ 2024 Heterogeneous Sets in Dimensionality Reduction and Ensemble Learning Henry W. J. Reeve, Ata Kabán, Jakramate Bootkrajang

ECML-PKDD 2024 Self-Certified Tuple-Wise Deep Learning Sijia Zhou, Yunwen Lei, Ata Kabán

MLJ 2024 Structure Discovery in PAC-Learning by Random Projections Ata Kabán, Henry W. J. Reeve

MLJ 2023 PAC-Learning with Approximate Predictors Andrew James Turner, Ata Kabán

NeurIPS 2023 Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms Sijia Zhou, Yunwen Lei, Ata Kaban

ECML-PKDD 2022 Noise-Efficient Learning of Differentially Private Partitioning Machine Ensembles Zhanliang Huang, Yunwen Lei, Ata Kabán

ICML 2020 Optimistic Bounds for Multi-Output Learning Henry Reeve, Ata Kaban

JAIR 2020 Structure from Randomness in Halfspace Learning with the Zero-One Loss Ata Kabán, Robert J. Durrant

AAAI 2019 Dimension-Free Error Bounds from Random Projections Ata Kabán

ALT 2019 Exploiting Geometric Structure in Mixture Proportion Estimation with Generalised Blanchard-Lee-Scott Estimators Henry Reeve, Ata Kabán

ICML 2019 Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise Henry Reeve, Ata Kaban

ALT 2017 On Compressive Ensemble Induced Regularisation: How Close Is the Finite Ensemble Precision Matrix to the Infinite Ensemble? Ata Kabán

ACML 2015 A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections Ata Kaban

ACML 2015 Non-Asymptotic Analysis of Compressive Fisher Discriminants in Terms of the Effective Dimension Ata Kaban

MLJ 2015 Random Projections as Regularizers: Learning a Linear Discriminant from Fewer Observations than Dimensions Robert J. Durrant, Ata Kabán

AISTATS 2014 New Bounds on Compressive Linear Least Squares Regression Ata Kabán

UAI 2013 Boosting in the Presence of Label Noise Jakramate Bootkrajang, Ata Kabán

ALT 2013 Dimension-Adaptive Bounds on Compressive FLD Classification Ata Kabán, Robert J. Durrant

ACML 2013 Random Projections as Regularizers: Learning a Linear Discriminant Ensemble from Fewer Observations than Dimensions Robert Durrant, Ata Kaban

ICML 2013 Sharp Generalization Error Bounds for Randomly-Projected Classifiers Robert Durrant, Ata Kaban

AISTATS 2012 Error Bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert Space Robert Durrant, Ata Kaban

ECML-PKDD 2012 Label-Noise Robust Logistic Regression and Its Applications Jakramate Bootkrajang, Ata Kabán

ECML-PKDD 2008 Learning with Lq<1 vs L1-Norm Regularisation with Exponentially Many Irrelevant Features Ata Kabán, Robert J. Durrant

MLJ 2007 Predictive Modelling of Heterogeneous Sequence Collections by Topographic Ordering of Histories Ata Kabán

ICML 2007 Robust Mixtures in the Presence of Measurement Errors Jianyong Sun, Ata Kabán, Somak Raychaudhury

ECML-PKDD 2006 Deconvolutive Clustering of Markov States Ata Kabán, Xin Wang

NeurIPS 2003 Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles Mark Girolami, Ata Kabán