Dr Christine Zarges


Research Groups


Chelly Dagdia, Z, Zarges, C, Beck, G & Lebbah, M 2020, 'A Scalable and Effective Rough Set Theory based Approach for Big Data Pre-processing', Knowledge and Information Systems, vol. 62, no. 8, pp. 3321-3386. https://doi.org/10.1007/s10115-020-01467-y
Chelly Dagdia, Z & Zarges, C 2020, 'A detailed study of the distributed rough set based locality sensitive hashing feature selection technique', Fundamenta Informaticae. https://doi.org/10.3233/FI-2016-0000
Major, L, Clare, A, Daykin, J, Mora, B, Peña Gamboa, L & Zarges, C 2020, Evaluation of a Permutation-Based Evolutionary Framework for Lyndon Factorizations. in T Bäck, M Preuss, A Deutz, H Wang, C Doerr, M Emmerich & H Trautmann (eds), Parallel Problem Solving from Nature – PPSN XVI: 16th International Conference, Leiden, The Netherlands, September 5-9, 2020, Proceedings. Lecture Notes in Computer Science, vol. 12269, Springer Nature, pp. 390-403, Parallel Problem Solving Nature, Leiden, Netherlands, 05 Sep 2020. https://doi.org/10.1007/978-3-030-58112-1_27
Paquete, L & Zarges, C (eds) 2020, Evolutionary Computation in Combinatorial Optimization: 20th European Conference, EvoCOP 2020, Held as Part of EvoStar 2020, Seville, Spain, April 15–17, 2020, Proceedings. Lecture Notes in Computer Science, vol. 12102, Springer Nature. https://doi.org/10.1007/978-3-030-43680-3
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.
More publications on the Research Portal