Walter Kosters

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

Curriculum Vitae

Recent talk (IPA, May 26, 2021): Combinatorial Game Theory — From Conway to Nash.

Research

• Member of the Algorithms group, headed by Professor Marcello Bonsangue.
• 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' 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.
  • Marijn Schraagen's PhD Thesis (defense: November 11, 2014), entitled Aspects of Record Linkage, within the LINKS project, see below.
  • Frank Takes' PhD Thesis (co-promotor; defense: November 19, 2014), entitled Algorithms for Analyzing and Mining Real-World Graphs, within the COMPASS project, see below.
  • Jiadong Lin's PhD Thesis (promotor; defense June 24, 2022), entitled Algorithms for Structural Variant Detection, within the Leiden-Xi'an CSC program.
  • Mark van den Bergh's PhD Thesis (promotor; defense June 1, 2023), entitled Imperfect Information Variants of Combinatorial Games.
  • Leon Helwerda's PhD Thesis (promotor; defense September 13, 2024), entitled Grip on Software.
  • Hanjo Boekhout's PhD Thesis (promotor; defense: summer 2025).
  Nominated for Leiden Science Faculty researcher of the year (see below for joint papers): 2014 — Frank Takes (for thesis); 2008 — Kai Ye; 2007 — Joost Broekens; 2006 — Joost Batenburg; 2005 — Siegfried Nijssen; 2004 — Ron Breukelaar.
• Co-organizer of ACG 2015, CG 2016, ACG 2017 and BNAIC/BeneLearn 2020.
• 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 (completed) project deals with data assistance for law enforcement.
• Together with Hendrik Jan Hoogeboom and Nies Huijsmans involved in the (completed) NWO financed LINKS project.
• Together with several others, in particular Toon Calders, involved in the (completed) NWO financed COMPASS project.
• 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. For part of the subject area, see the ICT.Open-IPA lecture in Rotterdam, October 23, 2012.
  The more recent publications deal with data mining and Artificial Intelligence.
• Generating and solving Nonograms. See lecture for IPA days in Vlijmen, April 13, 2011. And papers below. And also short lecture for highschool students: [Dutch] Bètadag, and a longer one: [Dutch] Gastles.
• 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.
  Recently updated! (Some improvements to be done ...)
• 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
  • WI 2005, IDA 2005, ICDM '05
  • SAC 2006, WI 2006, ICDM '06
  • SAC 2007, DMBiz '07, ECML/PKDD 2007, BNAIC 2007, ICDM '07, WI 2007
  • SAC 2008, CIARP 2008, BNAIC 2008, WI 2008, DDDM 2008
  • SAC 2009, IJCAI 2009, ICSOFT 2009, IDA 2009, ECML/PKDD 2009, WI 2009, BNAIC 2009, CIARP 2009, MWPR 2009, DDDM 2009
  • SAC 2010, IDA 2010, ICSOFT 2010, ICPR 2010, WI 2010, PRIB 2010, MCPR 2010, BNAIC 2010, CIARP 2010, ICDM 2010, DDDM 2010
  • SAC 2011, Benelearn 2011, MCPR 2011, ICSOFT 2011, WI 2011, ECML/PKDD 2011, PRIB 2011, BNAIC 2011, DDDM 2011, ICDM 2011
  • ICPRAM 2012, SAC 2012, PAKDD 2012, ICSOFT 2012, CIARP 2012, MCPR 2012, ECML-PKDD 2012, WI 2012, BNAIC 2012, ICDM 2012
  • ICPRAM 2013, SAC 2013, CIARP 2013, MCPR 2013, ICDM 2013, WI'13, ECML/PKDD 2013, BNAIC 2013
  • ICPRAM 2014, PAKDD 2014, SAC 2014 (EC), MCPR 2014, CIARP 2014, WI'14, ECML/PKDD 2014, BNAIC 2014
  • ICPRAM 2015, MCPR 2015, WI'15, ECML/PKDD 2015, ICDM 2015, ACG 2015, BNAIC 2015, SAC 2015 (EC), PAKDD 2015
  • ICPRAM 2016, WI'16, KDD 2016, MCPR 2016, ECML/PKDD 2016, CG 2016, BNAIC 2016, ICDM 2016
  • WI'17, ACG 2017, BNAIC 2017, ECML/PKDD 2017
  • ECML/PKDD 2018, CG 2018, BNAIC 2018, ACG 2019, BNAIC 2019, BNAIC 2020, BNAIC 2021, CoG2022, BNAIC 2022, BNAIC 2023

Teaching

• Responsible for a first year course on C++-programming: [Dutch] Programmeermethoden.
  Yearly some 250 first year students from the Faculty of Science (including computer scientists) take this 6 ECTS points course.
• Responsible for a course on artificial intelligence: [Dutch] Kunstmatige intelligentie.
  See also: [Dutch] lecture for Leiden film festival.
  This Bachelor course is also attractive for students from other departments, e.g., Psychology or Physics. And it is part of the minor Data Science.
• Organizing a student seminar on advanced algorithms, see Seminar (Combinatorial) Algorithms (Spring 2019/2024 and 2012/2017; related to the 2011 version: a presentation for an IPA event on May 26, 2021: Combinatorial Game Theory — From Conway to Nash, and two presentations at the IPA Advanced Course on Algorithmics and Complexity in Eindhoven, February 25, 2019, Gadgets in the Rush Hour and Algorithmic Game Theory) or 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.
• Some lectures on Bioinformatics (and data mining); see also a lecture for students from ICTinBusiness; and on Artificial Intelligence (AI) for psychologists. Also for [Dutch] parents.
• A lecture on Data Mining.
  For SIKS, in Zeist, Friday October 24, 2008
• Chairman of the Educational committee for Computer Science, see [Dutch] Opleidingscommissie Informatica until April 2014. After that: Program director of education for the bachelor Computer Science ([DUTCH] Programmadirecteur bachelor Informatica) until September 2020.
  
• Guiding student's Bachelor projects (and other projects, like Master projects, see below) in the area of data mining, or more general, AI. Until summer 2023 one of the organizers of the "Bachelorklas". See also: general lecture (old) on Data mining.
  
• (In the past ...) Providing one-hour lectures for highschool students, see [Dutch] Gastlessen. Also involved in the Pre-University College programme called LAPP-Top, and once in a while guiding high school projects. And interested in surreal numbers: lectures version 1, version 2 and version 3, or about Dots and boxes; also about science.
  Topics: backtracking and artificial intelligence.
• Received the "Education prize 2000-2001" from the Faculty. Again nominated in 2006 and 2013.
• 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.
    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. Not given at the moment.
  • Co-responsible for teaching assistants, see [Dutch] studentassistenten.
    TA's assist during bachelor courses.
• Advisor for bachelor and master theses.
• Interested in VN Detective en Thrillergids.

Publications

1. J. Lin, P. Jia, S. Wang, W. Kosters and K. Ye, Comparison and Benchmark of Structural Variants Detected from Long Read and Long-read Assembly, Briefings in Bioinformatics (2023) bbad188; doi.org/10.1093/bib/bbad188.
2. A. Plaat, W. Kosters and M. Preuss, High-Accuracy Model-Based Reinforcement Learning, A Survey; Artificial Intelligence Review 56, 9541–9573 (2023); doi.org/10.1007/s10462-022-10335-w.
3. J.K. Vis, M.A. Santcroos, W.A. Kosters and J.F.J. Laros, A Boolean Algebra for Genetic Variants, Bioinformatics 39 (2023) btad001; doi.org/10.1093/bioinformatics/btad001.
4. J. Lin, S. Wang, P.A. Audano, D. Meng, J.I. Flores, W. Kosters, X. Yang, P. Jia, T. Marschall, C.R. Beck and K. Ye, SVision: A Deep Learning Approach to Resolve Complex Structural Variants, Nature Methods 19, 1230-1233 (2022); doi.org/10.1038/s41592-022-01609-w.
5. M. van den Bergh, W. Kosters and F. Spieksma, Nim Variants, ICGA Journal 44, 2-17, 2022; doi.org/10.3233/ICG-220206.
6. J. Lin, X. Yang, W. Kosters, T. Xu, Y. Jia, S. Wang, Q. Zhu, M. Ryan, L. Guo, C. Zhang, C. Lee, S.E. Devine, E.E. Eichler and K. Ye, Mako: A Graph-based Pattern Growth Approach to Detect Complex Structural Variants. Genomics, Proteomics & Bioinformatics 20, 205-218, 2022; doi.org/10.1016/j.gpb.2021.03.007.
7. M. Baratchi, L. Cao, W.A. Kosters, J. Lijffijt, J.N. van Rijn and F.W. Takes, Artificial Intelligence and Machine Learning, 32nd Benelux Conference, BNAIC/Benelearn 2020, Leiden, The Netherlands, November 19–20, 2020, Revised Selected Papers; doi.org/10.1007/978-3-030-76640-5.
8. L. Cao, W.A. Kosters and J. Lijffijt, editors, Proceedings BNAIC/BeneLearn 2020, 19-20 November 2020, Leiden.
9. H.D. Boekhout, W.A. Kosters and F.W. Takes, Efficiently Counting Complex Multilayer Temporal Motifs in Large-scale Networks, Computational Social Networks (2019) 6: 8; doi:10.1186/s40649-019-0068-z.
10. H.D. Boekhout, W.A. Kosters and F.W. Takes, Counting Multilayer Temporal Motifs in Complex Networks, Complex Networks 2018: Complex Networks and Their Applications VII, pp. 565-577, Springer, 2018; doi:10.1007/978-3-030-05411-3_46.
11. F.W. Takes, W.A. Kosters, B. Witte and E.M. Heemskerk, Multiplex Network Motifs as Building Blocks of Corporate Networks, Applied Network Science 3: 39, Springer, 2018; doi:10.1007/s41109-018-0094-z.
12. M.H.M. Winands, H.J. van den Herik and W.A. Kosters (editors), Advances in Computer Games (ACG2017), LNCS 10664, 2017; doi:10.1007/978-3-319-71649-7.
13. F.J. Takes, W.A. Kosters and B. Witte, Detecting motifs in multiplex corporate networks, Complex Networks & Their Applications VI, Studies in Computational Intelligence 689, pp. 502-515. Springer 2017; doi:10.1007/978-3-319-72150-7_41.
14. K.J. Batenburg, L. Helwerda, W.A. Kosters and T. van der Meij, Agents for mobile radio tomography, In: Bosse T., Bredeweg B. (eds) BNAIC 2016: Artificial Intelligence. BNAIC 2016. Communications in Computer and Information Science, vol 765, pp. 63-75. Springer 2017; doi:10.1007/978-3-319-67468-1_5. (extended version of the conference paper below)
15. M.J.H. van den Bergh, A. Hommelberg, W.A. Kosters and F. Spieksma, Aspects of the cooperative card game Hanabi, In: Bosse T., Bredeweg B. (eds) BNAIC 2016: Artificial Intelligence. BNAIC 2016. Communications in Computer and Information Science, vol 765, pp. 93-105. Springer 2017; doi:10.1007/978-3-319-67468-1_7. (extended version of the conference paper below)
16. A. Plaat, J. van den Herik and W. Kosters (editors), Computers and Games (CG2016), LNCS 10068, 2016; doi:10.1007/978-3-319-50935-8.
17. M.J.H. van den Bergh, W.A. Kosters and F. Spieksma, Aspects of the cooperative card game Hanabi, BNAIC 2016, Amsterdam. Proceedings pages 25-32.
18. K.J. Batenburg, L. Helwerda, W.A. Kosters and T. van der Meij, Agents for mobile radio tomography, BNAIC 2016, Amsterdam. Proceedings pages 17-24.
19. H.J. van den Herik, W.A. Kosters and A. Plaat (editors), Recent Advances in Computer Games, special issue of Theoretical Computer Science, volume 644 (2016), pages 1-158; doi:10.1016/j.tcs.2016.07.026.
20. A. Plaat, J. van den Herik and W. Kosters (editors), Advances in Computer Games (ACG2015), LNCS 9525, 2015; doi:10.1007/978-3-319-27992-3.
21. M. Borassi, P. Crescenzi, M. Habib, W.A. Kosters, A. Marino and F.W. Takes, Fast diameter and radius BFS-based computation in (weakly connected) real-world graphs: With an application to the six degrees of separation games, Theoretical Computer Science 586 (2015), 59-80; doi:10.1016/j.tcs.2015.02.033.
22. H.J. Hoogeboom, W.A. Kosters, J. van Rijn and J.K. Vis, Acyclic Constraint Logic and Games, ICGA Journal 37 (2014), 3-16.
23. F.W. Takes and W.A. Kosters, Adaptive Landmark Selection Strategies for Fast Shortest Path Computation in Large Real-World Graphs, Proceedings of the 13th IEEE/WIC/ACM International Conference on Web Intelligence (WI 2014), Warsaw, pp. 27-34; doi:10.1109/WI-IAT.2014.13.
24. M. Schraagen and W.A. Kosters, Record Linkage using Graph Consistency, Machine Learning and Data Mining in Pattern Recognition (MLDM 2014), Saint Petersburg, LNAI 8556, pp. 471-483; doi:10.1007/978-3-319-08979-9_36.
25. M. Borassi, P. Crescenzi, M. Habib, W.A. Kosters, A. Marino and F.W. Takes, On the Solvability of the Six Degrees of Kevin Bacon Game — A Faster Graph Diameter and Radius Computation Method, Proceedings of the 7th International Conference on Fun with Algorithms (FUN 2014), LNCS 8496, pp. 52-63; doi:10.1007/978-3-319-07890-8_5.
26. G.H. Dal, W.A. Kosters and F.W. Takes, Fast Diameter Computation of Large Sparse Graphs using GPUs, Proceedings of the 22nd IEEE International Conference on Parallel, Distributed and Network-based Processing (PDP 2014), pp. 632-639; doi:10.1109/PDP.2014.17.
27. A. Terroba, W. Kosters, J. Varona and C.S. Manresa-Yee, Finding Optimal Strategies in Tennis from Video Sequences, International Journal of Pattern Recognition and Artificial Intelligence 27, number 6 (2013); doi:10.1142/S0218001413550100.
28. F.W. Takes and W.A. Kosters, Mining User-generated Path Traversal Patterns in an Information Network, Proceedings of the 12th IEEE/WIC/ACM International Conference on Web Intelligence (WI 2013), pp. 284-289; doi:10.1109/WI-IAT.2013.41.
29. F.W. Takes and W.A. Kosters, Computing the Eccentricity Distribution of Large Graphs, Algorithms 6 (2013), 100-118; doi:10.3390/a6010100.
30. K.J. Batenburg and W.A. Kosters, On the Difficulty of Nonograms, ICGA Journal 35 (2012), 195-205.
31. R.D. Chatham, M. Doyle, R.J. Jeffers, W.A. Kosters, R.D. Skaggs and J.A. Ward, Centrosymmetric Solutions to Chessboard Separation Problems, Bulletin of the Institute of Combinatorics and its Applications 65 (2012), 14 pages.
32. M. Luiten, W.A. Kosters and F.W. Takes, Topical Influence on Twitter: A Feature Construction Approach, The 24rd Benelux Conference on Artificial Intelligence (BNAIC 2012), 25-26 October 2012, Maastricht, The Netherlands. Proceedings pages 139-146.
33. M. Schraagen and W.A. Kosters, Data-driven Name Reduction for Record Linkage, Second International Conference on Innovative Computing Technology (INTECH 2012), 18-20 September 2012, Casablanca, Marocco.
34. F.W. Takes and W.A. Kosters, The Difficulty of Path Traversal in Information Networks, Fourth International Conference on Knowledge Discovery and Information retrieval (KDIR 2012), 4-7 October 2012, Barcelona, Spain. Proceedings pages 138-144.
35. K.J. Batenburg and W.A. Kosters, Nonograms, Nieuwsbrief van de Nederlandse Vereniging voor Theoretische Informatica (Newsletter of the Dutch Organization for Theoretical Computer Science), 16 (2012), 49-62.
36. F.W. Takes and W.A. Kosters, Identifying Prominent Actors in Online Social Networks using Biased Random Walks, The 23rd Benelux Conference on Artificial Intelligence (BNAIC 2011), 3-4 November 2011, Ghent, Belgium. Proceedings pages 215-222.
37. J.K. Vis, W.A. Kosters and K.J. Batenburg, Discrete Tomography: A Neural Network Approach, The 23rd Benelux Conference on Artificial Intelligence (BNAIC 2011), 3-4 November 2011, Ghent, Belgium. Proceedings pages 328-335.
38. F.W. Takes and W.A. Kosters, Determining the Diameter of Small World Networks, The 20th ACM Conference on Information and Knowledge Management, 24-28 October 2011, Glasgow, UK (CIKM 2011). Proceedings pages 1191-1196; doi:10.1145/2063576.2063748. (Also: 2 page abstract as ongoing work in Proceedings Benelearn 2011, pages 81-82.)
39. A.M. Kentsch, W.A. Kosters, P. van der Putten and F.W. Takes, Exploratory Recommendations Using Wikipedia's Linking Structure, Twentieth Belgian Dutch Conference on Machine Learning (Benelearn 2011), The Hague, The Netherlands, May 20, 2011; Proceedings, pages 61-68.
40. J.K. Vis, W.A. Kosters and A. Terroba, Tennis Patterns: Player, Match and Beyond, 22nd Benelux Conference on Artificial Intelligence (BNAIC 2010), Luxembourg, 25-26 October 2010.
41. F.W. Takes and W.A. Kosters, Applying Monte Carlo Techniques to the Capacitated Vehicle Routing Problem, 22nd Benelux Conference on Artificial Intelligence (BNAIC 2010), Luxembourg, 25-26 October 2010.
42. A. Terroba, W.A. Kosters and J.K. Vis, Tactical Analysis Modeling through Data Mining: Pattern Discovery in Racket Sports, International Conference on Knowledge Discovery and Information Retrieval (KDIR 2010), Valencia, Spain, 25-28 October 2010.
43. W. Pijls and W.A. Kosters, Mining Frequent Itemsets: A Perspective from Operations Research, Statistica Neerlandica 64 (2010) 367-387; doi:10.1111/j.1467-9574.2010.00452.x.
44. K.J. Batenburg, S. Henstra, W.A. Kosters and W.J. Palenstijn, Constructing Simple Nonograms of Varying Difficulty, Pure Mathematics and Applications (Pu.M.A.) 20 (2009), 1-15.
45. 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.
46. 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.
47. 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.
48. 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, pages 77-89, A. Gelbukh and E.F. Morales, eds.; doi:10.1007/978-3-540-88636-5_7.
49. 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.
50. 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 pages 81-88 (A. Nijholt, M. Pantic, M. Poel and H. Hondorp, editors).
51. 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 pages 387-388 (A. Nijholt, M. Pantic, M. Poel and H. Hondorp, editors).
52. 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.
53. 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, pages 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 pages 295-296 (A. Nijholt, M. Pantic, M. Poel and H. Hondorp, editors).
54. 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.
55. 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, pages 372-383, doi:10.1007/978-3-540-78275-9_33. See also a website for constructing Nonograms.
56. 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.
57. 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.
58. 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 pages 143-150 (M.M. Dastani and E. de Jong, editors).
59. 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 pages 189-195 (M.M. Dastani and E. de Jong, editors).
60. 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 pages 88-95 (M.M. Dastani and E. de Jong, editors).
61. 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, pages 13-20, Athens, Greece, 19-21 September 2007.
62. 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.
63. 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, pages 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 pages 329-330 (A. Nijholt, M. Pantic, M. Poel and H. Hondorp, editors).
64. 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, pages 267-280, Cambridge, UK, 10-12 December 2007.
65. 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), pages 357-366, 2007; doi:10.1007/978-3-540-73053-8_36.
66. 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.
67. 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 pages 171-177 (C.W. Clifton, N. Zhong, J. Liu, B.W. Wah and X. Wu, editors), Hong Kong, China, 18-22 December 2006.
68. 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 pages 149-155 (P.-Y. Schobbens, W. Vanhoof and G. Schwanen, editors).
69. 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 pages 59-66 (P.-Y. Schobbens, W. Vanhoof and G. Schwanen, editors).
70. 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 pages 291-298 (P.-Y. Schobbens, W. Vanhoof and G. Schwanen, editors).
71. 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 pages 90-93 (M. Ackermann, C. Soares and B. Guidemann, editors), Berlin, Germany, 22 September 2006.
72. 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 pages 16-27 (M. Hilarion and C. Nédellec, editors), Berlin, Germany, 18 September 2006.
73. 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), pages 511-525, 2006.
74. 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)), pages 389-403, 2006.
75. K.J. Batenburg and W.A. Kosters, Neural Networks for Discrete Tomography, BNAIC 2005, Brussels, Belgium, 17-18 October 2005; Proceedings pages 21-27 (K. Verbeeck, K. Tuyls, A. Nowé, B. Manderick and B. Kuijpers, editors).
76. 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 pages 81-88 (K. Verbeeck, K. Tuyls, A. Nowé, B. Manderick and B. Kuijpers, editors).
77. 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.), pages 13-24, 7 October 2005, Porto, Portugal.
78. J.M. de Graaf, R.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, pages 104-116).
79. H.J. Hoogeboom and W.A. Kosters, The Theory of Tetris, Nieuwsbrief van de Nederlandse Vereniging voor Theoretische Informatica (Newsletter of the Dutch Organization for Theoretical Computer Science), 9 (2005), 14-21.
80. H.J. Hoogeboom and W.A. Kosters, How to construct Tetris configurations, International Journal of Intelligent Games & Simulation (IJIGS), 3(2) 2005, 97-105; also: Technical Report 2003-8, LIACS, Universiteit Leiden.
81. 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.)
82. 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) pages 243-250).
83. 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, pages 1071-1080); poster small  | large — PPSN is a poster-only conference.
    Thanks to Leids Universiteits Fonds for a travel grant.
84. 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.
85. 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.
86. 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 pages 1001-1005).
87. 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.
88. 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).
89. R. Breukelaar, H.J. Hoogeboom and W.A. Kosters, Tetris is Hard, Made Easy, Technical Report 2003-9, LIACS, Universiteit Leiden, 2003.
90. 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), pages 331-338). (Upgraded version in Intelligent Data Analysis, see above.)
91. 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), pages 123-130).
92. 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, pages 284-292).
    Thanks to Leids Universiteits Fonds for a travel grant.
93. 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].
94. W.A. Kosters and M.C. van Wezel, Competitive Neural Networks for Customer Choice Models, pages 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].
95. 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), pages 115-122).
96. 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), pages 171-178).
97. 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), pages 355-362).
98. 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, pages 335-341.
    W.A. Kosters, Neural Networks for Data Mining, Chapter 6.2.8, pages 641-645.
99. 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, pages 145-155; Springer Lecture Notes in Computer Science 2189; editors: F. Hoffmann, D.J. Hand, N. Adams, D. Fisher and G. Guimaraes).
100. 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), pages 140-151).
101. J.M. de Graaf, W.A. Kosters and J.J.W. Witteman, Interesting Association Rules in Multiple Taxonomies (original version in PS), presented at BNAIC'00, Kaatsheuvel, November 1/2, 2000 (Proceedings (A. van den Bosch and H. Weigand, editors), pages 93-100); Interesting Association Rules in Multiple Taxonomies (slightly improved version in PDF).
102. 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), pages 165-172).
103. J.N. Kok and W.A. Kosters, Natural Data Mining Techniques, Bulletin of the EATCS 71, June 2000, pages 133-142. Also published in Current Trends in Theoretical Computer Science (editors G. Paun, G. Rozenberg and A. Salomaa), World Scientific, Singapore, 2001, pages 603-613.
104. 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 pages 323-328).
105. 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, pages 39-50; Springer Lecture Notes in Computer Science 1642; editors: D.J. Hand, J.N. Kok and M.R. Berthold).
106. W.A. Kosters, J.N. Kok and P. Floréen, Fourier Analysis of Genetic Algorithms, Theoretical Computer Science 229, 143-175, 1999.
107. 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), pages 221-228).
108. 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 (pages 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), pages 303-304).
109. T. Bäck, J.M. de Graaf, J.N. Kok and W.A. Kosters, Theory of Genetic Algorithms, Bulletin of the EATCS 63, October 1997, pages 161-192. Also published in Current Trends in Theoretical Computer Science (editors G. Paun, G. Rozenberg and A. Salomaa), World Scientific, Singapore, 2001, pages 546-578. An extended abstract is also available, originally written for the 1998 newspaper of the Dutch Organization for Theoretical Computer Science (NVTI), pages 27-35.
110. 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, pages 202-205 in Neural Networks: Best Practice in Europe, Proceedings Conference SNN'97, Amsterdam, May 22, 1997, published by World Scientific, Singapore, 1997.
111. 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 pages 97-102; also: Technical Report 96-35, Universiteit Leiden, 1996).
112. 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 pages 167-178 (H.F. Arner Jr., editor) and at SNN'97, Amsterdam, May 22, 1997; also: Technical Report 96-33, Universiteit Leiden, 1996.
113. J.M. de Graaf and W.A. Kosters, Expected Heights in Heaps, BIT 32 (1992), 570-579.
114. W.A. Kosters, Harmonic Analysis on Symmetric Spaces, PhD Thesis, Universiteit Leiden, 1985 (consisting of the Eigenspaces and the Symplectic papers below).
115. 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.)
116. W.A. Kosters, The Plancherel Formula for a Symplectic Symmetric Space, Technical Report 84-27, Universiteit Leiden, 1984.

Unpublished ;-)

1. L. Edixhoven and W. Kosters, Player preferences in N-player games, 2018; arXiv.
2. W.A. Kosters, Maze Traversals, Leiden, 2013.
3. H.J.M. Goeman and W.A. Kosters, Triangular Heaps, Universiteit Leiden, 1996.
4. J.M. de Graaf and W.A. Kosters, A Short Note on Hamiltonian Circuits in Subgraphs of the Triangulation Graph, Universiteit Leiden, 1988.
5. D. Bruin and W.A. Kosters, Lindstrom Scanning and Link Inversion, Universiteit Leiden, 1987.
6. W.A. Kosters, (f₄₍₄₎,so(4,5)): A Survey of Results and Problems, Universiteit Leiden, 1985.

Contact information

March 28, 2024 — http://www.liacs.leidenuniv.nl/~kosterswa/index.html