| ASCHEA: new results using adaptive segregational constraint handling SB Hamida, M Schoenauer Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat …, 2002 | 282 | 2002 |
| Recovering volatility from option prices by evolutionary optimization SB Hamida, R Cont Journal of Computational Finance 8 (4), 43-76, 2005 | 128* | 2005 |
| Evolutionary Algorithms A Petrowski, S Ben-Hamida John Wiley & Sons, 2017 | 105 | 2017 |
| An adaptive algorithm for constrained optimization problems S Ben Hamida, M Schoenauer International Conference on Parallel Problem Solving from Nature, 529-538, 2000 | 98 | 2000 |
| The need for improving the exploration operators for constrained optimization problems SB Hamida, A Petrowski Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No …, 2000 | 45 | 2000 |
| Selecting the best forecasting-implied volatility model using genetic programming W Abdelmalek, S Ben Hamida, F Abid Journal of Applied Mathematics and Decision Sciences 2009, 2009 | 23 | 2009 |
| Algorithmes évolutionnaires: prise en compte des contraintes et application réelle S Ben Hamida Ecole Polytechnique - France, 2001 | 18 | 2001 |
| Sampling Methods in Genetic Programming Learners from Large Datasets: A Comparative Study H Hmida, SB Hamida, A Borgi, M Rukoz Advances in Big Data - Proceedings of the 2nd {INNS} Conference on Big Data …, 2016 | 17 | 2016 |
| Scale Genetic Programming for large Data Sets: Case of Higgs Bosons Classification H Hmida, SB Hamida, A Borgi, M Rukoz Procedia Computer Science 126, 302-311, 2018 | 12 | 2018 |
| Hierarchical Data Topology Based Selection for Large Scale Learning H Hmida, S Ben Hamida, A Borgi, M Rukoz 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced …, 2016 | 11 | 2016 |
| Genetic Algorithm for Community Detection in Biological Networks MB M’Barek, A Borgi, W Bedhiafi, SB Hmida Procedia Computer Science 126, 195-204, 2018 | 9 | 2018 |
| Evolutionary Algorithms A Petrowski, S Ben Hamida Metaheuristics 1, 115-178, 2016 | 8 | 2016 |
| Adaptive sampling for active learning with genetic programming SB Hamida, H Hmida, A Borgi, M Rukoz Cognitive Systems Research 65, 23-39, 2021 | 7 | 2021 |
| Applying Dynamic Training‐Subset Selection Methods Using Genetic Programming for Forecasting Implied Volatility SB Hamida, W Abdelmalek, F Abid Computational Intelligence 32 (3), 369-390, 2016 | 6 | 2016 |
| Forecasting Financial Volatility Using Nested Monte Carlo Expression Discovery T Cazenave, SB Hamida Computational Intelligence, 2015 IEEE Symposium Series (CIFEr), 726-733, 2015 | 6 | 2015 |
| A logarithmic mutation operator to solve constrained optimization problems A Petrowski, SB Hamida Proceedings of the 1st Annual Conference on Genetic and Evolutionary …, 1999 | 6 | 1999 |
| Genetic Programming for Machine Learning A Pétrowski, S Ben‐Hamida Evolutionary Algorithms, 183-216, 2017 | 5 | 2017 |
| GA-PPI-Net: A genetic algorithm for community detection in protein-protein interaction networks M Ben M’barek, A Borgi, S Ben Hmida, M Rukoz Software Technologies: 14th International Conference, ICSOFT 2019, Prague …, 2020 | 4 | 2020 |
| Optimal quantization: Evolutionary algorithm vs stochastic gradient S BEN HAMIDA, M Mrad 9th Joint International Conference on Information Sciences (JCIS-06), 2006 | 4 | 2006 |
| Parametric coding vs genetic programming: A case study A Racine, S Ben Hamida, M Schoenauer Report-Software engineering, 13-22, 1999 | 4 | 1999 |
Marta Rukozchercheur, université Paris DauphineVerified email at lamsade.dauphine.fr
