Dr Christine Zarges
Lecturer
Department of Computer Science
Contact Details
- Email: chz8@aber.ac.uk
- ORCID: 0000-0002-2829-4296
- Office: E38, Llandinam Building
- Phone: +44 (0) 1970 622452
- Google Scholar: https://scholar.google.co.uk/citations?user=lDm_Kf4AAAAJ
- Research Portal Profile
Teaching
Module Coordinator
- CC21120 - Dylunio Rhaglen, Strwythurau Data a Algorithmau
- CS21120 - Program Design, Data Structures and Algorithms
Coordinator
- CC21120 - Dylunio Rhaglen, Strwythurau Data a Algorithmau
- CS21120 - Program Design, Data Structures and Algorithms
Tutor
- PGM2310 - Research Skills and Personal Development (Science) (2310)
- CC21120 - Dylunio Rhaglen, Strwythurau Data a Algorithmau
- CS21120 - Program Design, Data Structures and Algorithms
Lecturer
Research Groups
Publications
Clare, A, Daykin, J, Mills, T & Zarges, C 2019, 'Evolutionary Search Techniques for the Lyndon Factorization of Biosequences' Paper presented at Workshop on Evolutionary Computation for Permutation Problems at GECCO 2019, Prague, Czech Republic, 13 Jul 2019 - 17 Jul 2019, pp. 1543-1550.
Oliveto, PS, Sudholt, D & Zarges, C 2019, 'On the Benefits and Risks of Using Fitness Sharing for Multimodal Optimisation' Theoretical Computer Science, vol. 773, pp. 53-70. https://doi.org/10.1016/j.tcs.2018.07.007
Chelly Dagdia, Z, Zarges, C, Schannes, B, Micalef, M, Galiana, L, Rolland, B, de Fresnoye, O & Benchoufi, M 2019, Rough Set Theory as a Data Mining Technique: A Case Study in Epidemiology and Cancer Incidence Prediction. in U Brefeld, E Curry, E Daly, B MacNamee, A Marascu, F Pinelli, M Berlingerio & N Hurley (eds), Machine Learning and Knowledge Discovery in Databases: ECML PKDD 20-18. Lecture Notes in Computer Science , vol. 11053, Springer Nature, pp. 440-455, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Dublin, Ireland, 10 Sep 2018. https://doi.org/10.1007/978-3-030-10997-4_27
He, J, Jansen, T & Zarges, C 2019, Unlimited Budget Analysis. in Genetic and Evolutionary Computation Conference: Companion. Association for Computing Machinery, pp. 427-428, GECCO 2019: The Genetic and Evolutionary Computation Conference, Prague, Czech Republic, 13 Jul 2019.
Zamuda, A, Nicolau, M & Zarges, C 2018, A Black-Box Discrete Optimization Benchmarking (BB-DOB) Pipeline Survey: Taxonomy, Evaluation, and Ranking. in GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, pp. 1777-1782, GECCO 2018: The Genetic and Evolutionary Computation Conference, Kyoto, Japan, 15 Jul 2018.
More publications on the Research Portal