[13] | Data Integration in eHealth: A Domain/Disease Specific Roadmap (J Ure, R Proctor, M Martone, D Porteous, S Lloyd, S Lawrie, D Job, R Baldock, A Philp, D Liewald, F Rakebrand, A Blaikie, C McKay, S Anderson, J Ainsworth, van Hemert, J, I Blanquer, R Sinnott, C Barillot, F Bernard Gibaud, A Williams, M Hartswood, P Watson, L Smith, A Burger, J Kennedy, H Gonzalez-Velez, R Stevens, O Coecho, R Morton, P Linksted, M Deschenne, M McGilchrist, P Johnson, A Voss, R Gertz and J Wardlaw), In Studies in Health Technology and Informatics (N Jacq, Y Legré, H Muller, I Blanquer, V Breton, D Hausser, V Hernández, T Solomonides, M Hofman-Apitius, eds.), IOPress, volume 126, 2007. |
[12] | Binary Merge Model Representation of the Graph Colouring Problem (I Juhos, A Tóth and van Hemert, J), In Evol Comput in Comb Optim (J Gottlieb, G Raidl, eds.), Springer, 2004. |
[11] | A new permutation model for solving the graph k-coloring problem (I Juhos, A Tóth, M Tezuka, P Tann and van Hemert, J), In Kalmàr Workshop on Logic and Computer Science, 2003. |
[10] | Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems (J Eggermont and van Hemert, J), In Genetic Programming (J Miller, M Tomassini, PL Lanzi, C Ryan, AGB Tettamanzi, WB Langdon, eds.), Springer, 2001. |
[9] | Evolutionary Computation in Constraint Satisfaction and Machine Learning — An abstract of my PhD. (van Hemert, J), In Proceedings of the Brussels Evolutionary Algorithms Day (BEAD-2001) (Anne Defaweux, Bernard Manderick, Tom Lenearts, Johan Parent, Piet van Remortel, eds.), Vrije Universiteit Brussel (VUB), 2001. |
[8] | Stepwise Adaptation of Weights for Symbolic Regression with Genetic Programming (J Eggermont and van Hemert, J), In Proceedings of the Twelfth Belgium/Netherlands Conference on Artificial Intelligence (van den Bosch, A, H Weigand, eds.), 2000. |
[7] | Population dynamics and emerging features in AEGIS (AE Eiben, D Elia and van Hemert, J), In Proceedings of the Genetic and Evolutionary Computation Conference (W Banzhaf, J Daida, AE Eiben, MH Garzon, V Honavar, M Jakiela, RE Smith, eds.), Morgan Kaufmann Publishers, 1999. |
[6] | Adapting the Fitness Function in GP for Data Mining (J Eggermont, AE Eiben and van Hemert, J), In Genetic Programming (R Poli, P Nordin, WB Langdon, TC Fogarty, eds.), Springer, 1999. |
[5] | A comparison of genetic programming variants for data classification (J Eggermont, AE Eiben and van Hemert, J), In Advances in Intelligent Data Analysis (DJ Hand, JN Kok, MR Berthold, eds.), Springer, 1999. |
[4] | Comparing genetic programming variants for data classification (J Eggermont, AE Eiben and van Hemert, J), In Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (E Postma, M Gyssens, eds.), 1999. |
[3] | Mondriaan Art by Evolution (van Hemert, J and AE Eiben), In Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (E Postma, M Gyssens, eds.), 1999. |
[2] | Solving Binary Constraint Satisfaction Problems using Evolutionary Algorithms with an Adaptive Fitness Function (AE Eiben, van Hemert, J, E Marchiori and AG Steenbeek), In Parallel Problem Solving from Nature (AE Eiben, Th. Bäck, M Schoenauer, H-P Schwefel, eds.), Springer, 1998. |
[1] | Extended abstract: Solving Binary Constraint Satisfaction Problems using Evolutionary Algorithms with an Adaptive Fitness Function (AE Eiben, van Hemert, J, E Marchiori and AG Steenbeek), In Proceedings of the Xth Netherlands/Belgium Conference on Artificial Intelligence (NAIC'98) (la Poutré, JA, van den Herik, J, eds.), 1998. |