Ata Kaban

Colleges, School and Institutes

Willingness to take PhD students

Yes

PhD projects

Ata Kaban’s research interests include:

Statistical machine learning - theory and practice
High-dimensional data spaces
Probabilistic modelling of data, Bayesian inference
Large scale heuristic optimisation
Dimensionality reduction, random projections, compressive learning, compressive optimisation

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Most downloaded publications

Learning kernel logistic regression in the presence of class label noise
Ata Kaban, 1 Nov 2014, In : Pattern Recognition. 47, 11, p. 3641-3655 15 p.

Research output: Contribution to journal › Article

288 downloads
Special issue on advances in learning with label noise
Ata Kaban, 2015, In : Neurocomputing.

Research output: Contribution to journal › Editorial

180 downloads
Large scale continuous EDA using mutual information
Ata Kaban, 21 Nov 2016, Proceedings of the IEEE Congress on Evolutionary Computation. Institute of Electrical and Electronics Engineers (IEEE), 8 p. 16598

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

143 downloads
Compressive learning of multi-layer perceptrons: an error analysis
Ata Kaban, 30 Sep 2019, Proceedings of 2019 International Joint Conference on Neural Networks (IJCNN) . IEEE Computer Society Press, 7 p. N-20494

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

129 downloads
REMEDA: Random Embedding EDA for optimising functions with intrinsic dimension
Ata Kaban, 2016, Parallel Problem Solving from Nature – PPSN XIV: 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings. Springer, p. 859-868 10 p. (Lecture Notes in Computer Science; vol. 9921).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

129 downloads

Recent publications

Structure from Randomness in Halfspace Learning with the Zero-One Loss
Ata Kaban, 15 Sep 2020, (Accepted/In press) In : Journal of Artificial Intelligence Research. 32 p.

Research output: Contribution to journal › Article

Sufficient ensemble size for random matrix theory-based handling of singular covariance matrices
Ata Kaban, 17 Jul 2020, In : Analysis and Applications. 18, 5, p. 929-950 22 p.

Research output: Contribution to journal › Article

Optimistic Bounds for Multi-output Prediction
Henry Reeve & Ata Kaban, 1 Jun 2020, (Accepted/In press) 37th International Conference on Machine Learning (ICML 2020). 14 p.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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