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
Sanyang, M & Kaban, A 2019, 'Large scale estimation of distribution algorithms with adaptive heavy tailed random projection ensembles', Journal of Computer Science and Technology, vol. 34, no. 6, pp. 1241-1257. <http://jcst.ict.ac.cn/EN/10.1007/s11390-019-1973-1>
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. 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/>
Kaban, A 2019, Compressive learning of multi-layer perceptrons: an error analysis. in Proceedings of 2019 International Joint Conference on Neural Networks (IJCNN) ., N-20494, IEEE Computer Society Press, International Joint Conference on Neural Networks (IJCNN 2019), Budapest, Hungary, 14/07/19. https://doi.org/10.1109/IJCNN.2019.8851743
Kaban, A 2019, Dimension-free error bounds from random projections. in Thirty Third AAAI Conference on Artificial Intelligence (AAAI-19). Proceedings of the AAAI Conference on Artificial Intelligence, no. 1, vol. 33, AAAI Press, pp. 4049-4056, Thirty Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, Hawaii, United States, 27/01/19. https://doi.org/10.1609/aaai.v33i01.33014049
Reeve, HWJ & Kaban, A 2019, Exploiting geometric structure in mixture proportion estimation with generalised Blanchard-Lee-Scott estimators. in 30th International Conference on Algorithmic Learning Theory (ALT'19). Proceedings of Machine Learning Research, vol. 98, Proceedings of Machine Learning Research, pp. 682-699, 30th International Conference on Algorithmic Learning Theory (ALT'19), Chicago, United States, 22/03/19. <http://proceedings.mlr.press/v98/reeve19a.html>
Reeve, HWJ & Kaban, A 2019, Fast rates for a kNN classifier robust to unknown asymmetric label noise. in Proceedings of the Thirty-sixth International Conference on Machine Learning (ICML 2019). vol. 97, The Proceedings of Machine Learning Research , vol. 97, pp. 5401-5409, Thirty-sixth International Conference on Machine Learning (ICML 2019), Long Beach, CA, United States, 9/06/19. <http://proceedings.mlr.press/v97/reeve19a.html>
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