Kaan Demir

Kaan Demir profile picture

PhD Student
School of Engineering and Computer Science

Thesis Info

Research Interests: Multi-label Classification, Sparse Learning, Representation Learning
Thesis Title: Sparsity-based Feature Selection for Multi-label Classification
Supervisor: Prof Bing Xue, Dr Bach Nguyen

 

Publications

  1. K. Demir, et. al., "Co-operative Co-evolutionary Many-objective Embedded Multi-label Feature Selection with Decomposition-based PSO," In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '23). Association for Computing Machinery, New York, NY, USA, 438–446.
  2. K. Demir, et. al., "Particle swarm optimisation for sparsity-based feature selection in multi-label classification," In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '22). Association for Computing Machinery, New York, NY, USA, 232–235.
  3. K. Demir, et. al., 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.

  4. K. Demir, et. al., "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.
  5. K. Demir, et. al., "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.
  6. 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.