Recent publications
Article
Kaban, A & Palias, E 2024, 'A Bhattacharyya-type conditional error bound for quadratic discriminant analysis', Methodology and Computing in Applied Probability.
Huang, Z, Kaban, A & Reeve, H 2024, 'Efficient Learning with Projected Histograms', Data Mining and Knowledge Discovery. https://doi.org/10.1007/s10618-024-01063-6
Kaban, A & Reeve, H 2024, 'Structure discovery in PAC-Learning by Random Projections', Machine Learning. https://doi.org/10.1007/s10994-024-06531-0
Huang, Z, Lei, Y & Kaban, A 2023, 'Optimisation and Learning with Randomly Compressed Gradient Updates', Neural Computation. https://doi.org/10.1162/neco_a_01588
Turner, A & Kaban, A 2023, 'PAC learning with approximate predictors', Machine Learning. https://doi.org/10.1007/s10994-023-06301-4
Palias, E & Kabán, A 2023, 'The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification', Statistics and Computing, vol. 33, no. 4, 87. https://doi.org/10.1007/s11222-023-10251-1
Reeve, H, Kaban, A & Bootkrajang, J 2022, 'Heterogeneous sets in dimensionality reduction and ensemble learning', Machine Learning. https://doi.org/10.1007/s10994-022-06254-0
Kaban, A & Durrant, RJ 2020, 'Structure from Randomness in Halfspace Learning with the Zero-One Loss', Journal of Artificial Intelligence Research.
Kaban, A 2020, 'Sufficient ensemble size for random matrix theory-based handling of singular covariance matrices', Analysis and Applications, vol. 18, no. 5, pp. 929-950. https://doi.org/10.1142/S0219530520400072
Conference contribution
Palias, E & Kaban, A 2024, Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension. in 2024 International Joint Conference on Neural Networks (IJCNN). Proceedings of International Joint Conference on Neural Networks, IEEE, 2024 IEEE World Congress on Computational Intelligence, Yokohama, Japan, 30/06/24.
Zhou, S, Lei, Y & Kaban, A 2024, Self-certified Tuple-wise Deep Learning. in A Bifet, J Davis, T Krilavičius, M Kull, E Ntoutsi & I Žliobaitė (eds), Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2024, Vilnius, Lithuania, September 9–13, 2024, Proceedings, Part II. vol. 2, Lecture Notes in Computer Science, vol. 14942, Springer, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Vilnius, Lithuania, 9/09/24. https://doi.org/10.1007/978-3-031-70344-7_18
Huang, Z, Lei, Y & Kaban, A 2023, Noise-efficient learning of differentially private partitioning machine ensembles. in M-R Amin, S Canu, A Fischer, T Guns, PK Novak & G Tsoumakas (eds), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part IV. 1 edn, Lecture Notes in Computer Science, vol. 13716, Springer, Cham, pp. 587–603, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Genoble, France, 19/09/22. https://doi.org/10.1007/978-3-031-26412-2_36
Zhou, S, Lei, Y & Kaban, A 2023, Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms. in Advances in Neural Information Processing Systems: NeurIPS 2023. Advances in Neural Information Processing Systems, Thirty-seventh Conference on Neural Information Processing Systems, New Orleans, United States, 10/12/23.
Reeve, HWJ & Kaban, A 2020, Optimistic Bounds for Multi-output Prediction. in 37th International Conference on Machine Learning (ICML 2020). 37th International Conference on Machine Learning (ICML 2020), Virtual Event, 12/07/20.
Reeve, HWJ & Kaban, A 2019, Classification with unknown class-conditional label noise on non-compact feature spaces. in 32nd Annual Conference on Learning Theory (COLT 19). vol. 99, Proceedings of Machine Learning Research, vol. 99, Proceedings of Machine Learning Research, pp. 2624-2651, 32nd Annual Conference on Learning Theory (COLT 19), Phoenix, Arizona, United States, 25/06/19. <http://proceedings.mlr.press/v99/>
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