Christine Zarges

Lecturer

Contact Details

Room Number..........:  E38
Building....................:  Llandinam
Phone.......................:   +44 (0)1970 622452
E-Mail........................:   chz8

Research Groups

Teaching Areas

Modules Taught

  • CC21120: Dylunio Rhaglen, Strwythurau Data a Algorithmau
  • CS21120: Program Design, Data Structures and Algorithms
  • CS22120: Software Engineering

Publications

Theoretical Analysis of Lexicase Selection in Multi-Objective OptimizationJansen, T. & Zarges, C. 2018 (Accepted/In press) Parallel Problem Solving from Nature – PPSN XV: 15th International Conference, Coimbra, Portugal, September 8-12, 2018, Proceedings.Springer Nature, (Lecture Notes in Computer Science)
A Black-Box Discrete Optimization Benchmarking (BB-DOB) Pipeline Survey: Taxonomy, Evaluation, and RankingZamuda, A., Nicolau, M. & Zarges, C. 2018 (Accepted/In press) GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference Companion.Association for Computing Machinery
Nouveau Modèle de Sélection de Caractéristiques basé sur la Théorie des Ensembles Approximatifs pour les Données Massives: Méthode de sélection de caractéristiques pour les données massivesChelly Dagdia, Z., Zarges, C., Beck, G. & Lebbah, M. 2018 p. 377-3782 p.
Modèle de Sélection de Caractéristiques pour les Données Massives: Méthode de sélection de caractéristiques pour les données massivesChelly Dagdia, Z., Zarges, C., Beck, G. & Lebbah, M. 2018 15ème édition de l'atelier Fouille de Données Complexes: FDC.
A Distributed Rough Set Theory based Algorithm for an Efficient Big Data Pre-processing under the Spark FrameworkChelly Dagdia, Z., Zarges, C., Beck, G. & Lebbah, M. 2018 2017 IEEE International Conference on Big Data (Big Data). Nie, J-Y., Obradovic, Z., Suzumura, T., Ghosh, R., Nambiar, R., Wang, C., Zang, H., Baeza-Yates, R., Hu, X., Kepner, J., Cuzzocrea, A., Tang, J. & Toyoda, M. (eds.). IEEE Press, p. 911-916
Stability Selection using a Genetic Algorithm and Logistic Linear Regression on Healthcare RecordsZamuda, A., Zarges, C., Stiglic, G. & Hrovat, G. 2017 GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion. New York: Association for Computing Machinery, p. 143-1442 p.
Theoretical results on bet-and-run as an initialisation strategyLissovoi, A., Sudholt, D., Wagner, M. & Zarges, C. 2017 GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO). Bosman, P. A. N. (ed.). New York: Association for Computing Machinery, p. 857-8648 p.
On Easiest Functions for Mutation Operators in Bio-Inspired OptimisationCorus, D., He, J., Jansen, T., Oliveto, P. S., Sudholt, D. & Zarges, C. 2017 In : Algorithmica.78, 2, p. 714–740
Example Landscapes to Support Analysis of Multimodal OptimisationJansen, T. & Zarges, C. 2016 Proceedings 14th International Conference, Edinburgh UK, September 17-21, 2016. Handl, J., Hart, E., Lewis, P. R., López-Ibáñez , M., Ochoa, G. & Paechter, B. (eds.). Springer Nature, p. 792-802 (Lecture Notes in Computer Science; vol. 9921)
Analysis of Randomised Search Heuristics for Dynamic OptimisationJansen, T. & Zarges, C. 2015 In : Evolutionary Computation.23, 4, p. 513-54129 p.
Analysis of diversity mechanisms for optimisation in dynamic environments with low frequencies of changeOliveto, P. S. & Zarges, C. 2015 In : Theoretical Computer Science.561, p. 37-5620 p.
Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIIIHe, J. (ed.), Jansen, T. (ed.), Ochoa, G. (ed.) & Zarges, C. (ed.) 2015 Association for Computing Machinery.
On easiest functions for somatic contiguous hypermutations and standard bit mutationsCorus, D., He, J., Jansen, T., Oliveto, P., Sudholt, D. & Zarges, C. 2015 Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015). New York: Association for Computing Machinery, p. 1399-1406
Improving the performance of the Germinal center artificial immune system using ɛ-dominance: a multi-objective knapsack problem case studyJoshi, A., Rowe, J. E. & Zarges, C. 2015 Evolutionary Computation in Combinatorial Optimization: 15th European Conference, EvoCOP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. Ochoa, G. & Chicano, F. (eds.). Springer Nature, Vol. 9026, p. 114-12512 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics))
On the Effects of Incorporating Memory in GC-AIS for the Set Cover ProblemJoshi, A., Rowe, J. E. & Zarges, C. 2015 MIC 2015: The XI Metaheuristics International Conference.University of Lille 1
Reevaluating Immune-Inspired Hypermutations Using the Fixed Budget PerspectiveJansen, T. & Zarges, C. 2014 In : IEEE Transactions on Evolutionary Computation.18, 5, p. 674-68815 p.
Performance analysis of randomised search heuristics operating with a fixed budgetJansen, T. & Zarges, C. 2014 In : Theoretical Computer Science.545, p. 39-5820 p.
Artificial immune systems for optimisationJansen, T. & Zarges, C. 2014 GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference.Association for Computing Machinery, p. 749-76416 p.
Evolutionary algorithms and artificial immune systems on a bi-stable dynamic optimisation problemJansen, T. & Zarges, C. 2014 Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014). New York: Association for Computing Machinery, p. 975-982
On the runtime analysis of fitness sharing mechanismsOliveto, P. S., Sudholt, D. & Zarges, C. 2014 Parallel Problem Solving from Nature – PPSN XIII. Bartz-Beielstein, T., Branke, J., Filipič, B. & Smith, J. I. (eds.). Springer Nature, Vol. 8672, p. 932-94110 p. (Lecture Notes in Computer Science)
Understanding randomised search heuristics lessons from the evolution of theory: A case studyJansen, T. & Zarges, C. 2014 Proceedings of the 20th International Conference on Soft Computing (MENDEL 2014). Radek, M. (ed.). Brno University of Technology, p. 293-2986 p.
An immune-inspired algorithm for the set cover problemJoshi, A., Rowe, J. E. & Zarges, C. 2014 Parallel Problem Solving from Nature. Bartz-Beielstein, T., Branke, J., Filipič, B. & Smith, J. (eds.). Springer Nature, Vol. 8672, p. 243-2519 p. (Lecture Notes in Computer Science)
Mutation Rate Matters Even When Optimizing Monotonic FunctionsDoerr, B., Jansen, T., Sudholt, D., Winzen, C. & Zarges, C. 2013 In : Evolutionary Computation.21, 1, p. 1-27
Fixed budget computations: a different perspective on run time analysisJansen, T. & Zarges, C. 2012 GECCO '12 Proceedings of the 14th annual conference on Genetic and evolutionary computation. Soule, T. (ed.). Association for Computing Machinery, p. 1325-13328 p.
On the role of age diversity for effective aging operatorsJansen, T. & Zarges, C. 2011 In : Evolutionary Intelligence.4, 2, p. 99-12527 p.
Analyzing different variants of immune inspired somatic contiguous hypermutationsJansen, T. & Zarges, C. 2011 In : Theoretical Computer Science.412, 6, p. 517-53317 p.
On benefits and drawbacks of aging strategies for randomized search heuristicsJansen, T. & Zarges, C. 2011 In : Theoretical Computer Science.412, 6, p. 543-55917 p.