Selected Publications

2012
Duivesteijn, W., Feelders, A., Knobbe, A. Different Slopes for Different Folks - Mining for Exceptional Regression Models with Cook's Distance. In: Proceedings KDD 2012, 2012.
van Leeuwen, M. & Knobbe, A.J. Diverse Subgroup Set Discovery. In: Data Mining and Knowledge Discovery, special issue ECMLPKDD'12, pp 242-208, Springer, 2012.
2011
Knobbe, A., Feelders, A., Leman, D. Exceptional Model Mining, Data Mining: Foundations and Intelligent Paradigms 2, Holmes, D., Jain, L. (eds.), 2011.
van Leeuwen, M. & Knobbe, A.J. Non-Redundant Subgroup Discovery in Large and Complex Data. In: Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Data 2011 (ECML PKDD'11), 2011.
Bonchi, F., van Leeuwen, M. & Ukkonen, A. Characterizing Uncertain Data using Compression. In: Proceedings of the SIAM Conference on Data Mining 2011 (SDM'11), 2011.
Vreeken, J., van Leeuwen, M. & Siebes, A. Krimp: Mining Itemsets that Compress. In: Data Mining and Knowledge Discovery, vol.23(1), Springer, 2011.
2010
Duivesteijn, W., Knobbe, A.J., Feelders, A. & van Leeuwen, M. Subgroup Discovery meets Bayesian networks – an Exceptional Model Mining approach. In: Proceedings of the 10th IEEE International Conference on Data Mining (ICDM'10), 2010.
Feelders, A. Monotone Relabeling in Ordinal Classification. In: Proceedings of the 10th IEEE International Conference on Data Mining (ICDM'10), 2010.
van Leeuwen, M. Maximal Exceptions with Minimal Descriptions. In: Data Mining and Knowledge Discovery, special issue ECMLPKDD'10, vol.21(2), pp 259-276, Springer, 2010.
Kamphuis, C., Mollenhorst, E., Feelders, A., Pietersma, D. & Hogeveen, H. Decision-tree induction to detect clinical mastitis with automatic milking. In: Computers and Electronics in Agriculture, vol.70(1), pp 60-68, 2010.
2009
van Leeuwen, M., Bonchi, F., Sigurbjörnsson, B. & Siebes, A. Compressing Tags to Find Interesting Media Groups. In: Proceedings of the ACM Conference on Information and Knowledge Management (CIKM'09), pp 1147-1156, 2009.
van Leeuwen, M., Vreeken, J. & Siebes, A. Identifying the Components. In: Data Mining and Knowledge Discovery, special issue ECMLPKDD'09, vol.19(2), pp 176-193, Springer, 2009.
Barile, N. & Feelders, A. Nonparametric Ordinal Classification with Monotonicity Constraints. In: MoMo 2009, ECML PKDD'09 Workshop on Learning Monotone Models from Data, 2009.
van de Kamp, R., Feelders, A. & Barile, N. Isotonic Classification Trees. In: N. Adams, C. Robardet, A. Siebes & J.-F. Boulicaut (eds.) Advances in Intelligent Data Analysis VIII (IDA'09), Springer, pp 405-416, 2009.
Koopman, A. & Siebes, A. Characteristic Relational Patterns. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2009 (KDD'09), pp 437-446, 2009.
Heikinheimo, H., Vreeken, J., Siebes, A. & Mannila, H. Low-Entropy Set Selection. In: Proceedings of the SIAM International Conference on Data Mining (SDM'09), pp 569-579, 2009.
van der Gaag, L.C., Renooij, S., Feelders, A., de Groote, A., Eijkemans, M.J.C., Broekmans, F.J. & Fauser, B.C.J.M. Aligning Bayesian Network Classifiers with Medical Contexts. In: Proceedings of the MLDM'09, 2009.
2008
Barile, N. & Feelders, A. Nonparametric Monotone Classification with MOCA. In: Proceedings of the 8th IEEE International Conference on Data Mining (ICDM'08), 2008.
Tatti, N. & Vreeken, J. Finding Good Itemsets by Packing Data. In: Proceedings of the 8th IEEE International Conference on Data Mining (ICDM'08), pp 588-597, 2008.
Knobbe, A., Crémilleux, B., Fürnkranz, J. & Scholz, M. From Local Patterns to Global Models: the LeGo Approach to Data Mining. In: Fürnkranz, J. and Knobbe (eds.): From Local Patterns to Global Models: Proceedings of the ECML PKDD 2008 Workshop (LEGO'08), pp 1-16, 2008.
Duivesteijn, W. & Feelders, A. Nearest Neighbour Classification with Monotonicity Constraints. In: Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Data 2008 Part I (ECML PKDD'08), pp 301-316, 2008.
van Leeuwen, M. & Siebes, A. StreamKrimp: Detecting Change in Data Streams. In: Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Data 2008 Part II (ECML PKDD'08), pp 765-774, 2008.
Vreeken, J. & Siebes, A. Filling in the Blanks - Krimp Minimisation for Missing Data. In: Proceedings of the 8th IEEE International Conference on Data Mining (ICDM'08), pp 1067-1072, 2008.
Leman, D., Feelders, A. & Knobbe, A. Exceptional Model Mining. In: Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Data 2008 Part II (ECML PKDD'08), pp 1-16, 2008.
De Knijf, J. Mining Tree Patterns with Almost Smallest Supertrees. In: Proceedings of the SIAM Conference on Data Mining 2008 (SDM'08), 2008.
Koopman, A. & Siebes, A. Discovering Relational Item Sets Efficiently. In: Proceedings of the SIAM Conference on Data Mining 2008 (SDM'08), 2008.
Feelders, A. Credit Scoring, Chapter of: T. Rudas (ed.) Handbook of Probability: Theory and Applications, Sage, Los Angeles, 2008.
2007
de Jong, E.D. & Bucci, A. Objective Set Compression, Chapter of: J. Knowles, D. Corne, K. Deb & D. Raj (eds.) Multiobjective Problem Solving from Nature: From Concepts to Applications, Springer, Berlin, 2007.
Vreeken, J., van Leeuwen, M. & Siebes, A. Preserving Privacy through Data Generation. In: Proceedings of the IEEE Conference on Data Mining 2007 (ICDM'07), pp 685-690, 2007.
de Jong, E.D., Franke, L. & Siebes, A. On the Measurement of Genetic Interactions. In: Proceedings of the 3rd international symposium on Computational Life Science (CompLife'07), 2007.
van de Koppel, E., Slavkov, I., Astrahantseff, K., Schramm, A., Schulte, J., Vandesompele, J., de Jong, E., Dzeroski, S., Knobbe, A. Knowledge Discovery in Neuroblastoma-related Biological Data. In: Data Mining in Functional Genomics and Proteomics Workshop (DMFGP'07), pp 45-56, 2007.
De Knijf, J. & Feelders, A. Choosing the Right Patterns: An Experimental Comparison between Different Tree Inclusion Relations. In: D. Malerba, A. Appice and M. Ceci (editors), 6th Workshop on Multi-Relational Data Mining (MRDM'07), 2007.
Feelders, A. & van Straalen, R. Parameter Learning for Bayesian Networks with Strict Qualitative Influences. In: M.R. Berthold, J. Shawe-Taylor, N. Lavrac (eds.) Advances in Intelligent Data Analysis VII (IDA'07), Springer, pp 48-58, 2007.
Siebes, A., van Leeuwen, M. & Vreeken, J. MDL for Pattern Mining. In: Proceedings of the international conference on Statistics for Data Mining, Learning and Knowledge Extraction Models (IASC'07), 2007.
Vreeken, J., van Leeuwen, M. & Siebes, A. Characterising the Difference. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2007 (KDD'07), pp 765-774, 2007.
Feelders, A. A new Parameter Learning Method for Bayesian Networks with Qualitative Influences. In: R.Parr, L.C. van der Gaag (eds.) Proceedings of Uncertainty in Artificial Intelligence 2007 (UAI'07), AUAI Press, Corvallis (Oregon), pp 117-124, 2007.
Yo, T.-S. & de Jong, E.D. A comparison of evaluation methods in coevolution. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'07), pp 479-487, 2007.
de Jong, E.D. Objective Fitness Correlation. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'07), pp 440-447, 2007. (Best paper award, Coevolution track)
Wiering, M.A. & de Jong, E.D. Computing Optimal Stationary Policies for Multi-Objective Markov Decision Processes. In: Proceedings of the IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL'07), 2007.
De Knijf, J. FAT-miner: Mining Frequent Attribute Trees. In: Y. Cho, R. Wainwright, H. Haddad, S. Shin and Y. Koo (editors), Proceedings of the 2007 ACM symposium on Applied computing (SAC'07), 2007.
de Jong, E.D. A Monotonic Archive for Pareto-Coevolution. In: Evolutionary Computation, vol.15(1), pp 61-93, MIT Press, 2007.
Bosman, P.A.N & de Jong, E.D. Adaptation of a Success Story in GAs: Estimation-of-Distribution Algorithms for Tree-based Optimization Problems, Chapter of: Yang, A. & Shan, Y. (eds.) Success in Evolutionary Computation, Springer Verlag, Berlin, 2007.
Philippi, H. Sequence Alignment as a Database Technology Challenge. In: N. Revell, G. Pernull, R. Wagner (Ed.), Proceedings of the 2007 Conference on Database and Expert Systems Applications (DEXA'07), pp 459-468, 2007.
2006
Bathoorn, R., Koopman, A. & Siebes, A. Reducing the Frequent Pattern Set. In: Proceedings of the IEEE International Conference on Data Mining 2006, Workshops (ICDM-Workshops'06), pp 55-59, 2006.
Knobbe, A.J. & Ho, E.K.Y. Pattern Teams. In: Proceedings of the European Conference on Principles and Practice of Knowledge Discovery in Databases 2006 (PKDD'06), pp 577-584, 2006.
van Leeuwen, M., Vreeken, J. & Siebes, A. Compression Picks the Item Sets that Matter. In: Proceedings of the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'06), pp 585-592, 2006.
Feelders, A. & Ivanovs, J. Discriminative Scoring of Bayesian Network Classifiers: a Comparative Study. In: M. Studeny and J. Vomlel (eds.) Proceedings of the third European workshop on Probabilistic Graphical Models (PGM'06), pp 75-82, 2006.
de Jong, E.D. & Bucci, A. DECA: Dimension Extracting Coevolutionary Algorithm. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'06), 2006.
Oliehoek, F.A., de Jong, E.D. & Vlassis, N. The Parallel Nash Memory for Asymmetric Games. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'06), 2006.
Bosman, P.A.N. & de Jong, E.D. Combining gradient techniques for numerical multi-objective evolutionary optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'06), 2006.
Snijders, P., de Jong, E.D., de Boer, B. & Weissing, F. Multi-Objective Diversity Maintenance. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'06), 2006.
de Back, W., de Jong, E.D. & Wiering, M.A. Red Queen dynamics in a predator-prey ecosystem. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'06), 2006.
Siebes, A., Vreeken, J. & van Leeuwen, M. Item Sets That Compress. In: Proceedings of the SIAM Conference on Data Mining 2006 (SDM'06), pp 393-404, 2006.
Malik, R., Franke, L.H. & Siebes, A. Combination of text-mining algorithms increases the performance. In: Bioinformatics, vol.22(17), pp 2151-2157, 2006.
Knobbe, A.J. & Ho, E.K.Y. Maximally Informative k-Itemsets and their Efficient Discovery. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2006 (KDD'06), pp 244-253, 2006.
De Knijf, J. FAT-CAT: Frequent Attribute Tree Based Classification. In: N. Fuhr, M. Lalmas, and A. Trotman (editors), 5th International Workshop of the Initiative for the Evaluation of XML Retrieval (INEX'06), 2006.
Franke, L., van Bakel, H., Fokkens, L., de Jong, E.D., Egmont-Petersen, M. & Wijmenga, C. Gene Networks and Gene Prioritization. In: American Journal of Human Genetics, vol.78(), pp 1011-1025, 2006.
de Jong, E.D., Franke, L. & Siebes, A. A comparison of gene interaction measures. In: Proceedings of the International Conference on Research in Computational Molecular Biology (RECOMB'06), 2006.
de Jong, E.D. & Siebes, A. Evaluation of a Gene Network Extraction Method on Synthetic Data. In: Proceedings of the International Symposium on Networks in Biology (ISNB'06), 2006.
van Diggelen, J., de Jong, E.D. & Wiering, M.A. Strategies for Ontology Negotiation: Finding the Right Level of Generality. In: Proceedings of the International Workshop on Agent Communication at AAMAS'06 (IWAC'06), 2006.
Zwanepol Klinkmeijer, L. J., de Jong, E.D. & Wiering, M.A. A serial population genetic algorithm for dynamic optimization problems. In: Proceedings of the Annual Machine Learning Conference of Belgium and The Netherlands (BeNeLearn'06), 2006.
2005
Knobbe, A.J. Numbers in Multi-Relational Data Mining. In: Proceedings of the European Conference on Principles and Practice of Knowledge Discovery in Databases 2005 (PKDD'05), pp 544-551, 2005.
De Knijf, J. Frequent Tree Mining with Selection Constraints. In: S. Nijssen, T. Meinl and G. Karypis (editors), Proceedings of the Third International Workshop on Mining Graphs, Trees and Sequences (MGTS'05), 2005.
2004
De Knijf, J. & Feelders, A. Monotone Constraints in Frequent Tree Mining. In: M. van Otterlo, M. Poel and A. Nijholt (editors), Proceedings of the 14th Annual Machine Learning Conference of Belgium and the Netherlands (BeneLearn'04) , 2004.