Walter Kosters

Available subjects

• Curriculum vitae
• Research
• Teaching
• Publications
• Contact information

Curriculum Vitae

Research

• Member of the Algorithms group, headed by Professor J.N. Kok.
• Involved in the preparation of:
  • Michiel van Wezel's PhD Thesis (co-promotor; defense: March 7, 2002), entitled Neural networks for intelligent data analysis, Theoretical and experimental aspects;
  • Jeroen Eggermont's PhD Thesis, (co-promotor; defense: September 14, 2005), entitled Data mining using genetic programming.
  • Siegfried Nijssen's PhD Thesis, (co-promotor; defense: May 15, 2006), entitled Mining structured data.
  • Joost Broekens's PhD Thesis (co-promotor; defense: December 18, 2007), entitled Affect and learning — A computational analysis.
  • Edgar de Graaf's PhD Thesis (co-promotor; defense: October 29, 2008), entitled Mining semi-structured data, part of the NWO-MISTA project, see below.
  • Kai Ye's PhD thesis (co-promotor; defense: December 18, 2008), entitled Novel algorithms for protein sequence analysis.
  • Tim Cocx's PhD Thesis (co-promotor; defense: December 2, 2009), entitled Algorithmic Tools for Data-Oriented Law Enforcement, part of the NWO-ToKeN-DALE project, see below.
  • Jeroen Laros's PhD Thesis (co-promotor; defense: December 21, 2009), entitled Metrics and Visualisation for Crime Analysis and Genomics, part of the NWO-ToKeN-DALE project, see below.
  From these, nominated for Leiden Science Faculty researcher of the year: 2008 — Kai Ye; 2007 — Joost Broekens; 2006 — Joost Batenburg (see below for papers); 2005 — Siegfried Nijssen; 2004 — Ron Breukelaar (see below for papers).
• Project leader for the NWO financed MISTA project.
  This (completed) project deals with data mining in semi-structured data.
• Project leader for the NWO financed DALE project.
  This project deals with data assistance for law enforcement.
• Involved in several data mining research projects for the industry.
  Most of these projects deal with practical applications of data mining, and more in particular association rules (sometimes using fuzzy logic). In this case one is interested in finding hidden regularities in large amounts of electronically gathered data.
• Writing papers, see below.
  The more recent publications deal with data mining.
• Generating and solving Nonograms. See lecture for IPA/ASCI spring days in Helvoirt, April 16, 2009. And also short lecture for highschool students: [Dutch] Bètadag.
  Also known as Japanese puzzles, not to be confused with Sudoku.
• Playing Tetris. See also [Dutch] lecture.
  NP-completeness, constructability of configurations, decidability.
• Interested in heaps.
  An old friend.
• Still trying to place non-attacking queens on a chessboard (in particular rotation invariant positions), see our n-queens bibliography. Updated in February 2009!
• Co-organizer of the Workshop Harmonic Analysis and Homogeneous Spaces in Leiden, the Netherlands, 23-26 August 2004.
• Member of the Program Committee for
  • BNAIC 2004, The 16th Belgian-Dutch Conference on Artificial Intelligence, Groningen, the Netherlands, 21-22 October 2004.
  • Web Intelligence 2005, Compiegne, France, 19-22 September 2005.
  • IDA 2005, The 6th International Symposium on Intelligent Data Analysis, Madrid, Spain, 8-10 September 2005.
  • ICDM '05, The Fifth IEEE International Conference on Data Mining, Houston, Texas, USA, 27-30 November 2005.
  • SAC 2006, 21st Annual ACM Symposium on Applied Computing, Applications of Evolutionary Computation Track, Dijon, France, 23-27 April 2006.
  • Web Intelligence 2006, Hong Kong, 18-22 December 2006.
  • ICDM '06, The Sixth IEEE International Conference on Data Mining, Hong Kong, 18-22 December 2006.
  • SAC 2007, 22nd Annual ACM Symposium on Applied Computing, Evolutionary Computation Track, Seoul, Korea, March 11-15, 2007.
  • DMBiz'07, Data Mining for Business Workshop (co-located with PAKDD 2007), Nanjing, China, May 22-15, 2007.
  • ECML/PKDD 2007, The 18th European Conference on Machine Learning (ECML) and the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), Warsaw, Poland, September 17-21, 2007.
  • BNAIC 2007, The 19th Belgian-Dutch Conference on Artificial Intelligence, Utrecht, the Netherlands, November 5-6, 2007.
  • ICDM '07, The Seventh IEEE International Conference on Data Mining, Omaha, USA, 28-31 October 2007.
  • Web Intelligence 2007, Silicon Valley, USA, 2-5 November 2007.
  • SAC 2008, 23rd Annual ACM Symposium on Applied Computing, Evolutionary Computation Track, Vila Galé in Fortaleza, Ceará, Brazil, March 16-20, 2008.
  • CIARP 2008, 13th Iberoamerican Congress on Pattern Recognition, Havana, Cuba, September 9-12, 2008.
  • BNAIC 2008, the 20th Belgian-Dutch Conference on Artificial Intelligence, Enschede, the Netherlands, October 30-31, 2008.
  • Web Intelligence 2008, Sydney, Australia, December 9-12, 2008.
  • DDDM 2008, the Second International Workshop on Domain Driven Data Mining, Pisa, Italy, December 15, 2008.
  • SAC 2009, 24rd Annual ACM Symposium on Applied Computing, Evolutionary Computation Track, Hawaii, March 8-12, 2009.
  • IJCAI 2009, Twenty-first International Joint Conference on Artificial Intelligence, Pasadena, USA, July 11-17, 2009.
  • ICSOFT2009, The 4th International Conference on Software and Data Technologies, Sofia, Bulgaria, July 26-29, 2009.
  • IDA 2009, The 8th International Symposium on Intelligent Data Analysis, Lyon, France, August 31-September 2, 2009.
  • ECML/PKDD 2009, Bled, Slovenia, September 7-11, 2009.
  • Web Intelligence 2009, Milano, Italy, September 15-18, 2009.
  • BNAIC2009, the 21th Belgian-Dutch Conference on Artificial Intelligence, Eindhoven, the Netherlands, October 29-30, 2009.
  • CIARP 2009, 14th Iberoamerican Congress on Pattern Recognition, Guadalajara, Mexico, November 15-18, 2009.
  • MWPR2009, First Mexican Workshop on Pattern Recognition, Guadalajara City, Mexico, November 14, 2009.
  • DDDM 2009, the Third International Workshop on Domain Driven Data Mining, Miami, Florida, USA, December 6, 2009.
  • SAC 2010, 25th Annual ACM Symposium on Applied Computing, Evolutionary Computation Track, Sierre, Switzerland, March 22-26, 2010.
  • IDA 2010, The 9th International Symposium on Intelligent Data Analysis, Tucson, US, May 19-21, 2010.
  • ICSOFT2010, The 5th International Conference on Software and Data Technologies, Athens, Greece, July 22-24, 2010.:if expand("%") == ""|browse confirm w|else|confirm w|endif
  • ICPR 2010, 20th International Conference on Pattern Recognition, Istanbul, Turkey, August 23-26, 2010.

Teaching

• Responsible for a first year course on C++-programming: [Dutch] Programmeermethoden.
  Yearly some 150 first year students from the Faculty of Science (including computer scientists) take this 7 ECTS points course.
• Responsible for a course on artificial intelligence: [Dutch] Kunstmatige intelligentie.
  This Bachelor course is also attractive for students from other departments, e.g., Psychology or Physics.
• Organizing a student seminar on advanced algorithms, see Seminar Combinatorial Algorithms (Spring 2010). See also Seminar Artificial Intelligence and Complexity (Spring 2006; formerly known as [Dutch] Seminarium geavanceerde algoritmen; some time ago its main topic was BioComputing, see [Dutch] Seminarium Advanced BioComputing, Spring 2002). In Autumn 2008 it was: Seminar DNA String Algorithms.
  Topics change from year to year.
• Recent lectures on Bioinformatics (and data mining); see also a lecture for students form ICTinBusiness.
  Topic: fragment assembly.
• Recent lecture on Data Mining.
  For SIKS, in Zeist, Friday October 24, 2008
• Chairman of the Educational committee for Computer Science, see [Dutch] Opleidingscommissie Informatica.
  Complaints, ideas, ... please drop by.
• Guiding student's Bachelor projects (and other projects, see below) in the area of data mining, or more general, AI. See also: general lecture on Data mining.
  These projects usually take two or three months, and tackle a problem from the literature or the industry. They result in a short (10-20 pages) paper.
• Providing one-hour lectures for highschool students, see [Dutch] Gastlessen. Also involved in the Pre-University College programme called LAPP-Top, and also guiding high school projects. And interested in surreal numbers: lectures version 1, version 2 and version 3; also about science.
  Topics: backtracking and artificial intelligence.
• Received the "Education prize 2000-2001" from the Faculty. Again nominated in 2006.
• Some former activities:
  • Until September 2001: student advisor for first year students (Computer science).
    Including first contact meetings with new students, monitoring of results, advising students, supervising the schedule, PR, and so on.
  • Coordinator of the parttime Computer science curriculum.
    Including planning, scheduling and advising.
  • Responsible for the (old) Web pages of our Computer science curriculum.
    Planning, coordination, contents.
  • Co-responsible for a course on analysis of algorithms: [Dutch] Analyse van algoritmen.
    Master's course. Not given at the moment.
  • Co-responsible for a course on Java for Master students Mediatechnology, see [Dutch] Programmeren 1 - Java.
    Basic Java skills. Not given at the moment.
    For this same audience: a [Dutch] Javascript course.
  • Co-responsible for a short course on C++ for students Life Science & Technology, see [Dutch] Inleiding Programmeren (C++) - LS&T.
    Basic C++ skills.
  • Co-responsible for teaching assistants, see [Dutch] studentassistenten.
    TA's assist during bachelor courses.
• Advisor (usually one of the two advisors) for the following Master's Theses:
  • Peter van der Sman - Het effect van vertragingen voor treinreizigers: Het RVM-model (JdG; 1995)
  • Nico Knoops - Algoritmen voor het maken van roosters (IK; 1995)
  • Lex van den Nieuwenhuizen - Gestructureerd testen van objectgeorienteerd ontworpen systemen (GE; 1996)
  • Martel Berends - Attribuutselecte als basis voor datamining (IK; 1997)
  • Edzko Neuteboom - Begripvorming van klantgedrag met behulp van neurale netwerken (JK; 1997)
  • Maurits Out - Kostenschatting voor het wegbeheer met behulp van neurale netwerken (JK; 1997)
  • Michiel de Jong - Adaptive sampling - On the similarities between learning and evolving (AE; 1998)
  • Rokesh Jankie - Solving a university timetabling problem using local search (LK; 1998)
  • Jeroen Eggermont - Rule extraction and learning in the BP-SOM architecture (IS; 1998)
  • Bernard van Kesteren - The clustering problem in Dutch high schools; Changing metrics in search space (HG; 1999)
  • Gijsbert van Heurn - Het eindspel in het schaken: Van database tot regels (HG; 2000)
  • Siegfried Nijssen - Data mining using logic (JK; 2000)
  • Xander van Pelt - The fusion factory, a constrained data fusion approach (PvdP; 2001)
  • Daniel Palomo van Es - Fuzzy association rules and promotional sales data (JdG; 2001)
  • Jeroen Witteman - Frequent itemsets: taxonomies, interestingness, fuzzy logic and time behaviour (JdG; 2001)
  • Mischa Jansen - A scheduling simulator for LOFAR (JvH; 2001)
  • Joost Jacob - A scriptable planner: Using Python as a problem definition language (JvH; 2002)
  • Mathijs van der Burg - Genetic algorithms for Nonograms (HK; 2002)
  • Rogier van der Burg - Calculating supports for itemsets using a neural network (JdG; 2002)
  • Martijn van der Vaart - Distributed gameplaying using genetic programming (RK; 2002)
  • Jeroen Haverkorn van Rijsewijk - Evolution of game strategies using Genetic Programming (JdG; 2003)
  • Peter Koning - Neurale netwerken voor baggerschepen (MvW; 2003)
  • Julia Dmitrieva - Het toepassen van het TD(λ) algoritme op het spel vier-op-een-rij (JdG; 2003)
  • Joost Batenburg - An evolutionary algorithm for discrete tomography (HJH; 2003)
  • Niels Netten - Towards believable virtual characters using a computational model of emotion (DdG; 2004)
  • Lingjun Meng - Artificial immune system for knowledge discovery (PvdP; ICT in Business 2004)
  • Vedran Bilanovic - Temporal difference driving exam (HJH; 2004)
  • Tim Cocx - Automated generation and analysis of logical puzzles, The flats puzzle (JdG; 2004)
  • Pascal Haazebroek - Web event based usability analysis (HJH; 2004)
  • Jeroen Laros - Unique factors in the human genome (HJH, PT; 2005)
  • Sergio Prieto - Crime data mining (PvdP; ICT in Business 2005)
  • Lina Sun - Making the right offer to the right customer (PvdP; ICT in Business 2005)
  • Zhaochun Sun - EQPD, A way to improve the accuracy of mining fused data? (PvdP; ICT in Business 2005)
  • Wouter Meuleman - Integration and analysis of zebrafish microarray data (FV; 2005)
  • Robin Roestenburg - Particle Swarm Optimization: Finding optimal poker strategies (JMdG; 2005)
  • Martijn Cox - Simulated Evolution: A model of evolution focussing on neural networks (ME; 2006)
  • Chong Gao - Simulation and optimization in analytical and collaborative customer relationship management (PvdP; ICT in Business 2006)
  • Rui Chen - Application of collaborative filtering algorithm in bioinformatics (PvdP; ICT in Business 2006)
  • Daniil Umanski - Computer game development for speech therapy support (FV; MediaTechnology 2006)
  • Bastiaan Maat - The need for fusing head & neck cancer data (PvdP; ICT in Business 2006)
  • Staas de Jong - The retinal afterimage as information carrier (GV; VU 2006)
  • Tijn Witsenburg - Unravelling the genetic structure of NP-completeness (ME; 2006)
  • Matthijs van der Zon - Adding robustness and scalability to existing data mining algorithms for successful handling of large data sets (JK; 2006)
  • Ning Xu - Explanation interfaces in recommender systems (PvdP; ICT in Business 2007)
  • Alexander Nezhinsky - How rules determine the operator: Analysis of water height prediction (JdG; 2007)
  • Maarten Oosten - Verleden namen (HJH en KM; 2008)
  • Xuan Wang - An Empirical Study on the Relation between the Quality of UML Models and the Quality of the Implementation (MC; 2008)
  • Ron Vink - Temporal pattern analysis using reservoir computing (JK; 2009)
  • Timo de Vries - Predicting High-level Cognitive Decisions using Low-level Features from Eye Gaze Data (JB; 2009)
  Between brackets the name of the other advisor and the year are given. Abbreviations: JB: J. Broekens; MC: M.R.V. Chaudron; DdG: D. De Groot; AE: A.E. Eiben; ME: M.T.M. Emmerich; GE: G. Engels; HG: H.J.M. Goeman; JdG: J.M. de Graaf; JvH: J.I. van Hemert; HJH: H.J. Hoogeboom; LK: L.C.M. Kallenberg; RK: R. Keller; HK: H.C.M. Kleijn; JK: J.N. Kok; KM: K. Mandemakers; YO: Y.L. O; PvdP: P.W.H. van der Putten; IS: I.G. Sprinkhuizen-Kuyper; PT: P.H.K.G. Taschner; GV: G. van der Veer; FV: F. Verbeek; MvW: M.C. van Wezel.
  And Bachelor Theses for Tsoe Loong Li (2006), Sjoerd Henstra (2007), Robin van der Zwan (2007), Michiel Helvensteijn (2007; published as "Applying Data Mining to the Study of Joseki" at IFIP AI 2008 Milan, Italy, September 7-10, 2008; Proceedings; pp. 87-96; doi), Frank Takes (2008; published as Sokoban: Reversed Solving at NSVKI Student Conference, Utrecht, The Netherlands, June 6, 2008; Proceedings pp. 31-36), Susan Laraghy (2008) Jeroen Mets (2008), Ramon van Dam (2008), Bart van der Drift (2008), Johan Groenen (2008), Tim van Meurs (2008), Andrew Li (2008), Timo Morsink (2009), Kerem Denizmen (2009). And several ongoing ones ...
• And interested in VN Detective en Thrillergids.

Publications

1. W. Pijls and W.A. Kosters, Mining Frequent Itemsets: A Perspective from Operations Research, to appear, 2010.
2. K.J. Batenburg, S. Henstra, W.A. Kosters and W.J. Palenstijn, Constructing Simple Nonograms of Varying Difficulty, to appear, 2010.
3. J. Broekens, W.A. Kosters and T. de Vries, Eye Movements Disclose Decisions in Set, 21th Benelux Conference on Artificial Intelligence (BNAIC 2009), Eindhoven, The Netherlands, 29-30 October 2009; Proceedings (T. Calders, K. Tuyls and M. Pechenizkiy (editors)), pages 43-50.
4. F.W. Takes and W.A. Kosters, Solving SameGame and its Chessboard Variant, 21th Benelux Conference on Artificial Intelligence (BNAIC 2009), Eindhoven, The Netherlands, 29-30 October 2009; Proceedings (T. Calders, K. Tuyls and M. Pechenizkiy (editors)), pages 249-256.
5. K.J. Batenburg and W.A. Kosters, Solving Nonograms by Combining Relaxations, Pattern Recognition 42 (2009) 1672-1683; doi:10.1016/j.patcog.2008.12.003.
6. T.K. Cocx, W.A. Kosters and J.F.J. Laros, An Early Warning System for the Prediction of Criminal Careers, 7th Mexican International Conference on Artificial Intelligence (MICAI 2008), Atizapán de Zaragoza, Mexico, October 27-31, 2008; Proceedings LNCS 5317, pp. 77-89, A. Gelbukh and E.F. Morales, eds.; doi:10.1007/978-3-540-88636-5_7.
7. D. Umanski, W.A. Kosters, F.J. Verbeek and N. Schiller, Integrating Computer Games in Speech Therapy for Children Who Stutter, 1st Workshop on Child, Computer and Interaction, Chania, Crete, Greece, October 23, 2008.
8. E.H. de Graaf and W.A. Kosters, Visualizing Co-occurrence of Self-Optimizing Fragment Groups, 20th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2008), Enschede, The Netherlands, 30-31 October 2008; Proceedings pp. 81-88 (A. Nijholt, M. Pantic, M. Poel and H. Hondorp, editors).
9. K.J. Batenburg and W.A. Kosters, Automatic Generation of Japanese Puzzles, demo paper, 20th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2008), Enschede, The Netherlands, 30-31 October 2008; Proceedings pp. 387-388 (A. Nijholt, M. Pantic, M. Poel and H. Hondorp, editors).
10. J. Broekens, D. DeGroot and W.A. Kosters, Formal models of appraisal: Theory, specification, and computational model, Cognitive Systems Research 9 (2008), 173-197; doi:10.1016/j.cogsys.2007.06.007.
11. T.K. Cocx, W.A. Kosters and J.F.J. Laros, Temporal Extrapolation within a Static Clustering, 17th International Symposium on Methodologies for Intelligent Systems (ISMIS'08), Toronto, Canada, May 21-23, 2008; Proceedings (editors An, A.; Matwin, S.; Ras, Z.W.; Slezak, D.); Springer LNAI 4994, pp. 189-195, doi:10.1007/978-3-540-68123-6_21.
    See also 2 page overview, at the 20th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2008), Enschede, The Netherlands, 30-31 October 2008; Proceedings pp. 295-296 (A. Nijholt, M. Pantic, M. Poel and H. Hondorp, editors).
12. T.K. Cocx, W.A. Kosters and J.F.J. Laros, Enhancing the Automated Analysis of Criminal Careers, Workshop on Link Analysis, Counterterrorism, and Security (LATCS) at the SIAM International Data Mining Conference, Atlanta, USA, April 26, 2008.
13. K.J. Batenburg and W.A. Kosters, A Reasoning Framework for Solving Nonograms, International Workshop on Combinatorial Image Analysis (IWCIA 2008), Buffalo, USA, April 7-9, 2008; Proceedings: LNCS 4958, pp. 372-383, doi:10.1007/978-3-540-78275-9_33. See also a website for constructing Nonograms.
14. E.H. de Graaf, J.N. Kok and W.A. Kosters, Mining Balanced Patterns in Web Access Data, The IASTED International Conference on Artificial Intelligence and Applications (AIA 2008), Proceedings paper 595-147 (A. Gammerman, editor), February 11-13, 2008, Innsbruck, Austria.
15. H.J. Hoogeboom, J.F.J. Laros and W.A. Kosters, Selection of DNA Markers, IEEE Transactions on Systems, Man, and Cybernetics, Part C, 38, 26-32, 2008; doi:10.1109/TSMCC.2007.906060.
16. E.H. de Graaf, J.N. Kok and W.A. Kosters, Displaying Co-occurrences of Patterns in Streams for Website Usage Analysis, 19th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2007), Utrecht, The Netherlands, 5-6 October 2007; Proceedings pp. 143-150 (M.M. Dastani and E. de Jong, editors).
17. W.A. Kosters and J.F.J. Laros, Visualization on a Closed Surface, 19th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2007), Utrecht, The Netherlands, 5-6 October 2007; Proceedings pp. 189-195 (M.M. Dastani and E. de Jong, editors).
18. T.K. Cocx and W.A. Kosters, Adapting and Visualizing Association Rule Mining Systems for Law Enforcement Purposes, 19th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2007), Utrecht, The Netherlands, 5-6 October 2007; Proceedings pp. 88-95 (M.M. Dastani and E. de Jong, editors).
19. E.H. de Graaf, J.N. Kok and W.A. Kosters, Clustering Improves the Exploration of Graph Mining Results, Artificial Intelligence and Innovations 2007: from Theory to Applications, Proceedings of the 4th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI07), C. Boukis, A. Pnevmatikakis and L. Polymenakos (eds.), Springer, pp. 13-20, Athens, Greece, 19-21 September 2007.
20. J. Broekens, W.A. Kosters and F.J. Verbeek, On affect, anticipation and adaptation: Investigating the potential of affect-controlled selection of anticipatory simulation in artificial adaptive agents, Adaptive Behavior 15 (2007) 397-422; doi:10.1177/1059712307084686.
21. W.A. Kosters and J.F.J. Laros, Metrics for Mining Multisets, Research and Development in Intelligent Systems XXIV, Proceedings of AI-2007, the Twenty-seventh SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (M. Bramer, F. Coenen, M. Petridis, editors), Springer, pp. 293-303, Cambridge, UK, 10-12 December 2007.
    See also 2 page overview, at the 20th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2008), Enschede, The Netherlands, 30-31 October 2008; Proceedings pp. 329-330 (A. Nijholt, M. Pantic, M. Poel and H. Hondorp, editors).
22. E.H. de Graaf, J. Kazius, J.N. Kok and W.A. Kosters, Visualization and Grouping of Graph Patterns in Molecular Databases, Research and Development in Intelligent Systems XXIV, Proceedings of AI-2007, the Twenty-seventh SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence (M. Bramer, F. Coenen, M. Petridis, editors), Springer, pp. 267-280, Cambridge, UK, 10-12 December 2007.
23. J. Broekens, W.A. Kosters and F.J. Verbeek, On Affect and Self-Adaptation: Potential Benefits of Valence-Controlled Action-Selection, 2nd International Work-Conference on the Interplay between Natural and Artificial Computation (IWINAC2007), Murcia (Spain), June 18-21, Lecture Notes in Artificial Intelligence 4527 (J. Mira and J.R. Álvarez, editors), pp. 357-366, 2007; doi:10.1007/978-3-540-73053-8_36.
24. K. Ye, W.A. Kosters and A.P. IJzerman, An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences, Bioinformatics 23 (2007) 687-693; doi:10.1093/bioinformatics/btl665.
25. J.S. de Bruin, T.K. Cocx, W.A. Kosters, J.F.J. Laros and J.N. Kok, Data Mining Approaches to Criminal Career Analysis, Sixth IEEE International Conference on Data Mining (ICDM 2006), Proceedings pp. 171-177 (C.W. Clifton, N. Zhong, J. Liu, B.W. Wah and X. Wu, editors), Hong Kong, China, 18-22 December 2006.
26. E.H. de Graaf and W.A. Kosters, Mining for Stable Patterns: Regular Intervals between Occurrences, 18th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2006), Namur, Belgium, 5-6 October 2006; Proceedings pp. 149-155 (P.-Y. Schobbens, W. Vanhoof and G. Schwanen, editors).
27. J. Broekens, T. Cocx and W.A. Kosters, Object-Centered Interactive Multi-Dimensional Scaling: Ask the Expert, 18th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2006), Namur, Belgium, 5-6 October 2006; Proceedings pp. 59-66 (P.-Y. Schobbens, W. Vanhoof and G. Schwanen, editors).
28. C. Soares, E.H. de Graaf, J.N. Kok and W.A. Kosters, Sequence Mining on Web Access Logs: A Case Study, 18th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC 2006), Namur, Belgium, 5-6 October 2006; Proceedings pp. 291-298 (P.-Y. Schobbens, W. Vanhoof and G. Schwanen, editors).
29. J.S. de Bruin, T.K. Cocx, W.A. Kosters, J.F.J. Laros and J.N. Kok, Onto Clustering of Criminal Careers, ECML/PKDD-2006 Workshop on Practical Data Mining: Applications, Experiences and Challenges, Proceedings pp. 90-93 (M. Ackermann, C. Soares and B. Guidemann, editors), Berlin, Germany, 22 September 2006.
30. E.H. de Graaf, J.M. de Graaf and W.A. Kosters, Using Consecutive Support for Genomic Profiling, ECML/PKDD-2006 Workshop on Data and Text Mining for Integrative Biology, Proceedings pp. 16-27 (M. Hilarion and C. Nédellec, editors), Berlin, Germany, 18 September 2006.
31. T.K. Cocx and W.A. Kosters, A Distance Measure for Determining Similarity between Criminal Investigations, 6th Industrial Conference on Data Mining (ICDM) 2006, 14-15 July, Leipzig, Germany, Lecture Notes in Artificial Intelligence 4065 (P. Perner, editor), pp. 511-525, 2006.
32. K.J. Batenburg and W.A. Kosters, A Neural Network Approach to Real-time Discrete Tomography, International Workshop on Combinatorial Image Analysis (IWCIA) 2006, Berlin, Germany, 19-21 June, Lecture Notes in Computer Science 4040, (Ralf Reulke, Ulrich Eckardt, Boris Flach, Uwe Knauer, Konrad Polthier (editors)), pp. 389-403, 2006.
33. K.J. Batenburg and W.A. Kosters, Neural Networks for Discrete Tomography, BNAIC 2005, Brussels, Belgium, 17-18 October 2005; Proceedings pp. 21-27 (K. Verbeeck, K. Tuyls, A. Nowé, B. Manderick and B. Kuijpers, editors).
34. E.H. de Graaf and W.A. Kosters, Efficient Feature Detection for Sequence Classification in a Receptor Database, BNAIC 2005, Brussels, Belgium, 17-18 October 2005; Proceedings pp. 81-88 (K. Verbeeck, K. Tuyls, A. Nowé, B. Manderick and B. Kuijpers, editors).
35. E.H. de Graaf and W.A. Kosters, Using a Probable Time Window for Efficient Pattern Mining in a Receptor Database, Proceedings of the Third International Workshop on Mining Graphs, Trees and Sequences MGTS2005 (S. Nijssen, T. Meinl and G. Karypis, eds.), pp. 13-24, 7 October 2005, Porto, Portugal.
36. J.M. de Graaf, Renée X. de Menezes, J.M. Boer and W.A. Kosters, Frequent Itemsets for Genomic Profiling, Computational Life Sciences, First International Symposium, CompLife 2005, Konstanz, Germany, 25-27 September 2005 (Proceedings (M.R. Berthold, R. Glen, K. Diederichs, O. Kohlbacher and I. Fischer, editors), LNCS 3695, pp. 104-116).
37. H.J. Hoogeboom and W.A. Kosters, The Theory of Tetris, Nieuwsbrief van de Nederlandse Vereniging voor Theoretische Informatica (Newspaper of the Dutch Organization for Theoretical Computer Science), 9 (2005), 14-21.
38. M.C. van Wezel and W.A. Kosters, Nonmetric Multidimensional Scaling: Neural Networks Versus Traditional Techniques, Intelligent Data Analysis 8 (2004), 601-613. (Upgraded version of BNAIC2003 paper below.)
39. K.J. Batenburg and W.A. Kosters, A Discrete Tomography Approach to Japanese Puzzles, presented at BNAIC 2004, 21-22 October 2004, Groningen, The Netherlands (Proceedings (R. Verbrugge, N. Taatgen and L. Schomaker, editors) pp. 243-250).
40. H.J. Hoogeboom and W.A. Kosters, How to construct Tetris configurations, International Journal of Intelligent Games & Simulation (IJIGS), 3(2) 2004, 94-102; also: Technical Report 2003-8, LIACS, Universiteit Leiden.
41. J. Eggermont, J.N. Kok and W.A. Kosters, Detecting and Pruning Introns for Faster Decision Tree Evolution, presented at PPSN VIII, Birmingham, UK, 18-22 September 2004 (Proceedings (X. Yao, E. Burke, J.A. Lozano, J. Smith, J.J. Merelo-Guervós, J.A. Bullinaria, J. Rowe, P. Tino, A. Kabán and H.-P. Schwefel, editors), LNCS 3242, pp. 1071-1080); poster small  | large — PPSN is a poster-only conference.
    Thanks to Leids Universiteits Fonds for a travel grant.
42. R. Breukelaar, E.D. Demaine, S. Hohenberger, H.J. Hoogeboom, W.A. Kosters, and D. Liben-Nowell. Tetris is Hard, Even to Approximate, International Journal of Computational Geometry and Applications (IJCGA) 14 (2004), 41-68.
43. M. Prudencio, J. Rohovec, J. A. Peters, E. Tocheva, M. J. Boulanger, M. E. P. Murphy, H. J. Hupkes, W.A. Kosters, A. Impagliazzo and M. Ubbink, A caged lanthanide complex as paramagnetic shift agent for protein NMR, Chemistry - A European Journal 10 (2004), 3252-3260.
44. J. Eggermont, J.N. Kok and W.A. Kosters, Genetic Programming for Data Classification: Partitioning the Search Space, presented at the 19th Annual ACM Symposium on Applied Computing (SAC'04), Nicosia, Cyprus, March 14-17, 2004 (Proceedings pp. 1001-1005).
45. H.J. Hoogeboom and W.A. Kosters, Tetris and Decidability, Information Processing Letters 89 (2004), 267-272; also: Technical Report 2003-10, LIACS, Universiteit Leiden.
46. W.A. Kosters and W. Pijls, Apriori: A Depth First Implementation, presented (by Bart Goethals) at FIMI'03, the first Workshop on Frequent Itemset Mining Implementations, November 19, 2003, Melbourne, Florida, USA (CEUR Workshop Proceedings, ISSN 1613-0073, online; Bart Goethals and Mohammed J. Zaki (eds.)); see also more on the algorithm (including the current implementation).
47. R. Breukelaar, H.J. Hoogeboom and W.A. Kosters, Tetris is Hard, Made Easy, Technical Report 2003-9, LIACS, Universiteit Leiden, 2003.
48. M.C. van Wezel and W.A. Kosters, Nonmetric Multidimensional Scaling: Neural Networks Versus Traditional Techniques, presented at BNAIC 2003, October 23/24, 2003, Nijmegen, The Netherlands (Proceedings (T. Heskes, P. Lucas, L. Vuurpijl and W. Wiegerinck, editors), pp. 331-338). (Upgraded version in Intelligent Data Analysis, see above.)
49. J. Eggermont, J.N. Kok and W.A. Kosters, Genetic Programming for Data Classification: Refining the Search Space, presented at BNAIC 2003, October 23/24, 2003, Nijmegen, The Netherlands (Proceedings (T. Heskes, P. Lucas, L. Vuurpijl and W. Wiegerinck, editors), pp. 123-130).
50. W.A. Kosters, W. Pijls and V. Popova, Complexity Analysis of Depth First and FP-growth Implementations of Apriori, presented at MLDM 2003 (Machine Learning and Data Mining in Pattern Recognition), Leipzig, Germany, July 5-7, 2003 (Proceedings (P. Perner and A. Rosenfeld, editors), Lecture Notes in Artificial Intelligence 2734, Springer, pp. 284-292).
    Thanks to Leids Universiteits Fonds for a travel grant.
51. M.C. van Wezel and W.A. Kosters, Numerical Integration by Cubature Formulae in Bayesian Neural Networks, presented at ICONIP2003, Istanbul, Turkey, June 2003 (Supplementary Proceedings ICANN/ICONIP, pages 82-85) [upgraded version of the BNAIC 2002 paper below].
52. W.A. Kosters and M.C. van Wezel, Competitive Neural Networks for Customer Choice Models, pp. 41-60 in J. Segovia, P.S. Szczepaniak and M. Niedzwiedzinski, editors, E-Commerce and Intelligent Methods, Studies in Fuzziness and Soft Computing 105, Physica-Verlag, Springer, 2002 [enhanced version of the PADD'97 paper below].
53. J.M. de Graaf, W.A. Kosters, W. Pijls and V. Popova, A Theoretical and Practical Comparison of Depth First and FP-growth Implementations of Apriori, presented at BNAIC 2002, October 21/22, 2002, Leuven, Belgium (Proceedings (H. Blockeel and M. Denecker, editors), pp. 115-122).
54. R.E. Keller, W.A. Kosters, M. van der Vaart and M.D.J. Witsenburg, Genetic Programming Produces Strategies for Agents in a Dynamic Environment, presented at BNAIC 2002, October 21/22, 2002, Leuven, Belgium (Proceedings (H. Blockeel and M. Denecker, editors), pp. 171-178).
55. M.C. van Wezel and W.A. Kosters, Numerical Integration by Cubature Formulae in Bayesian Neural Networks, presented at BNAIC 2002, October 21/22, 2002, Leuven, Belgium (Proceedings (H. Blockeel and M. Denecker, editors), pp. 355-362).
56. Two chapters in Dealing with the Data Flood: Mining Data, Text and Multimedia (J. Meij, editor), STT/Beweton, Den Haag, 2002 (publication STT 65):
    L. Kwee and W.A. Kosters, Future Cases: Data Mining in Virtual Organizations, Chapter 3.3.2, pp. 335-341.
    W.A. Kosters, Neural Networks for Data Mining, Chapter 6.2.8, pp. 641-645.
57. M.C. van Wezel, W.A. Kosters, P. van der Putten and J.N. Kok, Nonmetric Multidimensional Scaling with Neural Networks, presented at IDA 2001 (Advances in Intelligent Data Analysis), The Fourth International Conference, Cascais, Portugal, September 13/15, 2001 (Proceedings, pp. 145-155; Springer Lecture Notes in Computer Science 2189; editors: F. Hoffmann, D.J. Hand, N. Adams, D. Fisher and G. Guimaraes).
58. J.M. de Graaf, W.A. Kosters and J.J.W. Witteman, Interesting Fuzzy Association Rules in Quantitative Databases, presented at PKDD 2001 (The 5th European Conference on Principles of Data Mining and Knowledge Discovery), Freiburg, Germany, September 3/5, 2001 (Proceedings Springer Lecture Notes in Artificial Intelligence 2168 (L. De Raedt and A. Siebes, editors), pp. 140-151).
59. J.M. de Graaf, W.A. Kosters and J.J.W. Witteman, Interesting Association Rules in Multiple Taxonomies, presented at BNAIC'00, Kaatsheuvel, November 1/2, 2000 (Proceedings (A. van den Bosch and H. Weigand, editors), pp. 93-100).
60. M.C. van Wezel, M.D. Out and W.A. Kosters, Ensembles of Nonconformist Neural Networks, presented at BNAIC'00, Kaatsheuvel, November 1/2, 2000 (Proceedings (A. van den Bosch and H. Weigand, editors), pp. 165-172).
61. J.N. Kok and W.A. Kosters, Natural Data Mining Techniques, Bulletin of the EATCS 71, June 2000, pp. 133-142. Also published in Current Trends in Theoretical Computer Science (editors G. Paun, G. Rozenberg and A. Salomaa), World Scientific, Singapore, 2001, pp. 603-613.
62. M.D. Out and W.A. Kosters, A Bayesian Approach to Combined Neural Networks Forecasting, presented at ESANN'2000 (The 8th European Symposium on Artificial Neural Networks), Brugge, April 26/28, 2000 (Proceedings pp. 323-328).
63. W.A. Kosters, E. Marchiori and A. Oerlemans, Mining Clusters with Association Rules, presented at IDA99 (The Third Symposium on Intelligent Data Analysis), Amsterdam, August 9/11, 1999 (Proceedings, pp. 39-50; Springer Lecture Notes in Computer Science 1642; editors: D.J. Hand, J.N. Kok and M.R. Berthold).
64. W.A. Kosters, J.N. Kok and P. Floréen, Fourier Analysis of Genetic Algorithms, Theoretical Computer Science 229, 143-175, 1999.
65. M.B. de Jong and W.A. Kosters, Adaptive Sampling, presented at NAIC'98, Amsterdam, November 18/19, 1998 (Proceedings (H. La Poutré and J. van den Herik, editors), pp. 221-228).
66. M.C. van Wezel, W.A. Kosters and J.N. Kok, Maximum Likelihood Weights for a Linear Ensemble of Regression Neural Networks, Proceedings ICONIP'98 (pp. 498-501 (S. Usui and T. Omori, editors)), Japan, October 1998. A short survey was presented at NAIC'98, Amsterdam, November 18/19, 1998 (Proceedings (H. La Poutré and J. van den Herik, editors), pp. 303-304).
67. T. Bäck, J.M. de Graaf, J.N. Kok and W.A. Kosters, Theory of Genetic Algorithms, Bulletin of the EATCS 63, October 1997, pp. 161-192. Also published in Current Trends in Theoretical Computer Science (editors G. Paun, G. Rozenberg and A. Salomaa), World Scientific, Singapore, 2001, pp. 546-578. An extended abstract is also available, originally written for the 1998 newspaper of the Dutch Organization for Theoretical Computer Science (NVTI), pp. 27-35.
68. M.C. van Wezel, A.E. Eiben, C.M.H. van Kemenade, J.N. Kok, W.A. Kosters and I.G. Sprinkhuizen-Kuyper, Natural Solutions to Practical Problems: An Overview of Marketing, Scheduling and Information Filtering Problems Solved by Neural and Evolutionary Techniques, pp. 202-205 in Neural Networks: Best Practice in Europe, Proceedings Conference SNN'97, Amsterdam, May 22, 1997, published by World Scientific, Singapore, 1997.
69. M.C. van Wezel, J.N. Kok and W.A. Kosters, Two Neural Network Methods for Multidimensional Scaling, presented at ESANN'97 (European Symposium on Artificial Neural Networks), Brugge, April 16/18, 1997 (Proceedings pp. 97-102; also: Technical Report 96-35, Universiteit Leiden, 1996).
70. W.A. Kosters, J.A. La Poutré and M.C. van Wezel, Understanding Customer Choice Processes Using Neural Networks, presented at PADD'97 (First International Conference on the Practical Application of Knowledge Discovery and Data Mining), London, April 24/25, 1997 (Proceedings pp. 167-178 (H.F. Arner Jr., editor) and at SNN'97, Amsterdam, May 22, 1997; also: Technical Report 96-33, Universiteit Leiden, 1996.
71. H.J.M. Goeman and W.A. Kosters, Triangular Heaps, Universiteit Leiden, 1996. (unpublished)
72. J.M. de Graaf and W.A. Kosters, Expected Heights in Heaps, BIT 32 (1992), 570-579.
73. J.M. de Graaf and W.A. Kosters, A Short Note on Hamiltonian Circuits in Subgraphs of the Triangulation Graph, Universiteit Leiden, 1988. (unpublished)
74. D. Bruin and W.A. Kosters, Lindstrom Scanning and Link Inversion, Universiteit Leiden, 1987. (unpublished)
75. W.A. Kosters, (f₄₍₄₎,so(4,5)): A survey of results and problems, Universiteit Leiden, 1985. (unpublished)
76. W.A. Kosters, Harmonic Analysis on Symmetric Spaces, PhD Thesis, Universiteit Leiden, 1985 (consisting of the Eigenspaces and the Symplectic papers below).
77. W.A. Kosters, Eigenspaces of the Laplace-Beltrami-operator on SL(n,R)/S(GL(1)xGL(n-1)), Part I, Indagationes Mathematicae 47 (1985), 99-123; Part II, Indagationes Mathematicae 47 (1985), 125-145. (Also: Technical Report 84-8, Universiteit Leiden, 1984.)
78. W.A. Kosters, The Plancherel Formula for a Symplectic Symmetric Space, Technical Report 84-27, Universiteit Leiden, 1984.

Contact information

Questions/remarks: kosters@liacs.nl.

January 22, 2010 — http://www.liacs.nl/home/kosters/index.html