Kaan Demir
PhD Student
School of Engineering and Computer Science
Thesis Info
Research Interests: Multi-label Classification, Feature Selection, Sparsity Regularisation, Sparse Coding, Evolutionary Computation
Thesis Title: Sparsity-based Feature Selection for Multi-label Classification
Supervisor: Prof Bing Xue, Dr Bach Nguyen
Thesis Title: Sparsity-based Feature Selection for Multi-label Classification
Supervisor: Prof Bing Xue, Dr Bach Nguyen
Publications
- K. Demir, B. H. Nguyen, B. Xue, and M. Zhang, "A Decomposition based Multi-objective Evolutionary Algorithm with ReliefF based Local Search and Solution Repair Mechanism for Feature Selection," 2020 IEEE Congress on Evolutionary Computation (CEC), Glasgow, UK, 2020, pp. 1-8.
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K. Demir, B. H. Nguyen, B. Xue, and M. Zhang. 2021. Sparsity-based evolutionary multi-objective feature selection for multi-label classification. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '21). Association for Computing Machinery, New York, NY, USA, 147–148.
- K. Demir, B. H. Nguyen, B. Xue and M. Zhang, "Multi-objective Multi-label Feature Selection with an Aggregated Performance Metric and Dominance-based Initialisation," 2021 IEEE Congress on Evolutionary Computation (CEC), 2021, pp. 760-767.
- K. Demir, B. H. Nguyen, B. Xue and M. Zhang, "Multi-objective Feature Selection with a Sparsity-based Objective Function and Gradient Local Search for Multi-label Classification," 2021 International Conference on Data Mining Workshops (ICDMW), 2021, pp. 823-832, doi: 10.1109/ICDMW53433.2021.00106.