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| [18] | The DATA Bonanza: Improving Knowledge Discovery for Science, Engineering and Business (MP Atkinson, R Baxter, P Brezany, O Corcho, M Galea, J van Hemert, M Parsons and D Snelling), John Wiley & Sons, 2013, 576 pages. |
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| [17] | EnzML: multi-label prediction of enzyme classes using InterPro signatures (L De Ferrari, S Aitken, J van Hemert and I Goryanin), In BMC Bioinformatics, volume 13, 2012. |
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| [16] | A Generic Parallel Processing Model for Facilitating Data Mining and Integration (L Han, CS Liew, Malcolm PA and van Hemert, JI), In Parallel Computing, Elsevier, volume 37, 2011. |
| [15] | Performance database: capturing data for optimizing distributed streaming workflows (Liew, C, Atkinson, M, ..., van Hemert, J and Han, L), In Philos T R Soc A, volume 369, 2011. |
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| [14] | A distributed architecture for data mining and integration (Atkinson, MP, van Hemert, J, Han, L, Hume, A and Liew, CS), In Data-Aware Distributed Computing, ACM, volume 2, 2009. |
| [13] | An E-infrastructure to Support Collaborative Embryo Research (Barker, A, van Hemert, J, Baldock, RA and Atkinson, MP), In Cluster Computing and the Grid, IEEE Computer Society, volume 9, 2009. |
| [12] | Automating Gene Expression Annotation for Mouse Embryo (Han, L, Atkinson, MP, Baldock, RA and van Hemert, J), In Advanced Data Mining and Applications, volume 5, 2009. |
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| [11] | Matching Spatial Regions with Combinations of Interacting Gene Expression Patterns (van Hemert, J and RA Baldock), In BioInformatics Research and Development (M Elloumi, \emphet al., eds.), Springer, volume 2, 2008. |
| [10] | A Novel Visual Discriminator for Network Traffic Patterns (Han, L and van Hemert, J), In Advanced Engineering Computing and Applications in Sciences, volume 2, 2008. |
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| [9] | Mining spatial gene expression data for association rules (van Hemert, J and RA Baldock), In BioInformatics Research and Development (S Hochreiter, R Wagner, eds.), Springer, volume 4414, 2007. |
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| [8] | Application of Evolutionary Computation to Constraint Satisfaction and Data Mining (van Hemert, J), PhD thesis, Leiden University, 2002. |
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| [7] | 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. |
| [6] | 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. |
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| [5] | 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. |
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| [4] | 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. |
| [3] | 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. |
| [2] | 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. |
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| [1] | Applying Adaptive Evolutionary Algorithms to Hard Problems (van Hemert, J), Master's thesis, Leiden University, 1998. |