ALG2004.bib

@INPROCEEDINGS{Henkel04,
  AUTHOR = {C. Henkel and G. Rozenberg and H. Spaink},
  EDITOR = {C. Ferretti and G. Mauri and C. Zandron},
  TITLE = {Application of mismatch detection methods in {DNA} computing},
  BOOKTITLE = {preliminary proceedings DNA10, June 2004, Milano},
  PAGES = {183-192},
  YEAR = {2004}
}


@ARTICLE{Hoogeboom04,
  AUTHOR = {H.J. Hoogeboom and W.A. Kosters},
  TITLE = {Tetris and Decidability},
  JOURNAL = {Information Processing Letters},
  VOLUME = {89},
  PAGES = {267-272},
  YEAR = {2004}
}


@ARTICLE{Hoogeboom04a,
  AUTHOR = {H.J. Hoogeboom and W.A. Kosters},
  TITLE = {How to Construct Tetris Configurations},
  JOURNAL = {International Journal of Intelligent Games and Simulation},
  VOLUME = {3},
  PAGES = {94-102},
  YEAR = {2004}
}


@TECHREPORT{Breukelaar03,
  AUTHOR = {R. Breukelaar and H.J. Hoogeboom and W.A. Kosters},
  TITLE = {Tetris is Hard, Made Easy},
  TYPE = {LIACS Technical Report},
  INSTITUTION = {Leiden Institute of Advanced Computer Science (LIACS)},
  VOLUME = {2003-09},
  YEAR = {2003},
  ANNOTE = {http://www.liacs.nl/home/kosters/tetris/tetr.pdf"Technical Report}
}


@INPROCEEDINGS{Breukelaar04,
  AUTHOR = {R. Breukelaar and E.D. Demaine and S. Hohenberger and H.J. Hoogeboom and W.A. Kosters and D. Liben-Nowell},
  EDITOR = {D.T. Lee and J.S.B. Mitchell},
  TITLE = {Tetris is Hard, Even to Approximate},
  BOOKTITLE = {Special Issue: Selected Papers from the Ninth International Computing    and Combinatorics Conference (COCOON 2003), Big Sky, MT, USA, July 2003},
  PAGES = {41-68},
  YEAR = {2004},
  NOTE = {Published as International Journal of Computational Geometry and Applications, volume 14}
}


@INPROCEEDINGS{Schmidt03,
  AUTHOR = {K.A. Schmidt and C.V. Henkel and G. Rozenberg and H.P. Spaink},
  EDITOR = {J. Chen and J. Reif},
  TITLE = {Experimental Single-Molecule {DNA} Computing},
  BOOKTITLE = {Proceedings Ninth International Meeting    on DNA Based Computers (DNA9), 1-4 June 2003, Madison, Wisconsin, USA},
  PAGES = {191},
  YEAR = {2003}
}


@INPROCEEDINGS{Baumlck03,
  AUTHOR = {Th. Bäck and J.N. Kok and G. Rozenberg},
  EDITOR = {L.F. Landweber and E. Winfree},
  TITLE = {Evolutionary Computation as a Paradigm for {DNA}-Based Computing},
  BOOKTITLE = {Evolution as Computation,     DIMACS Workshop, Princeton, January 1999},
  SERIES = {Natural Computing Series},
  PAGES = {15-40},
  PUBLISHER = {Springer},
  YEAR = {2003}
}


@INPROCEEDINGS{EKK04,
  AUTHOR = {J. Eggermont and J.N. Kok and W.A. Kosters},
  TITLE = {Genetic Programming for Data Classification: {P}artitioning the Search Space},
  BOOKTITLE = {Proceedings of the 2004 Symposium on applied computing (ACM SAC'04)},
  YEAR = {2004},
  PAGES = {1001-1005},
  ADDRESS = {Nicosia, Cyprus},
  MONTH = {14-17 } # MAR,
  ORGANISATION = {ACM},
  KEYWORDS = {genetic programming, data classification},
  SIZE = {5 pages},
  ABSTRACT = {When Genetic Programming is used to evolve decision trees for data classification, search spaces tend to become extremely large. We present several methods using techniques from the field of machine learning to refine and thereby reduce the search space sizes for decision tree evolvers. We will show that these refinement methods improve the classification performance of our algorithms. }
}


@INPROCEEDINGS{EKK04b,
  AUTHOR = {J. Eggermont and J.N. Kok and W.A. Kosters},
  TITLE = {Detecting and Pruning Introns for Faster Decision Tree Evolution},
  BOOKTITLE = {Parallel Problem Solving from Nature - PPSN VIII},
  YEAR = {2004},
  PAGES = {1071-1080},
  ADDRESS = {Birmingham, United Kingdom},
  MONTH = {18-22 },
  KEYWORDS = {genetic programming, data classification},
  SIZE = {10 pages},
  SERIES = {LNCS},
  VOLUME = {3242},
  PUBLISHER = {Springer-Verlag},
  ABSTRACT = {We show how the understandability and speed of genetic programming classification algorithms can be improved, without affecting the classification accuracy. By analyzing the decision trees evolved we can remove the unessential parts, called {\it introns}, from the discovered decision trees. Since the resulting trees contain only useful information they are smaller and easier to understand. Moreover, by using these pruned decision trees in a fitness cache we can significantly reduce the number of unnecessary fitness calculations.}
}


@INPROCEEDINGS{NK04a,
  AUTHOR = {Siegfried Nijssen and Joost N. Kok},
  TITLE = {A Quickstart in Frequent Structure Mining Can Make a Difference},
  BOOKTITLE = {Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD2004, Seattle, USA, August 22-25, 2004},
  PUBLISHER = {ACM Press},
  EDITOR = {Ronny Kohavi and Johannes Gehrke and William DuMouchel and Joydeep Ghosh},
  PAGES = {647-652},
  YEAR = {2004},
  ABSTRACT = {Given a database, structure mining algorithms search for substructures that satisfy constraints such as minimum frequency, minimum confidence, minimum interest and maximum frequency. Examples of substructures include graphs, trees and paths. For these substructures many mining algorithms have been proposed. In order to make graph mining more efficient, we investigate the use of the ``quickstart principle'', which is based on the fact that these classes of structures are contained in each other, thus allowing for the development of structure mining algorithms that split the search into steps of increasing complexity. We introduce the GrAph/Sequence/Tree extractiON ({\sc Gaston}) algorithm that implements this idea by searching first for frequent paths, then frequent free trees and finally cyclic graphs. We investigate two alternatives for computing the frequency of structures and present experimental results to relate these alternatives.}
}


@INPROCEEDINGS{NK04b,
  AUTHOR = {Siegfried Nijssen and Joost N. Kok},
  TITLE = {Ideal Refinement of Datalog Clauses Using Primary Keys},
  BOOKTITLE = {Proceedings of the 16th European Conference on Artificial Intelligence, ECAI2004, Valencia, Spain, August 22-27, 2004},
  PUBLISHER = {IOS Press},
  EDITOR = {Ramon L{\'o}pez de M{\'a}ntaras and Lorenza Saitta},
  PAGES = {520-524},
  YEAR = {2004}
}


@INPROCEEDINGS{NK04c,
  AUTHOR = {Siegfried Nijssen and Joost N. Kok},
  TITLE = {Frequent Graph Mining and its Application to Molecular Databases},
  BOOKTITLE = {Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, SMC 2004, Den Haag, Netherlands, October 10-13, 2004},
  PUBLISHER = {IEEE Press},
  ABSTRACT = {Molecular fragment mining is a promising approach for discovering novel fragments for drugs. We in-vestigate a method for mining fragments which consists of three phases: first, a preprocessing phase for turning molec-ular databases into graph databases; second, the {\sc Gaston} frequent graph mining phase for mining frequent paths, free trees and cyclic graphs; and third, a postprocessing phase in which redundant frequent fragments are removed. We will devote most of our attention to the frequent graph mining phase, as this phase is computationally the most demanding, but will also look at the other phases.},
  YEAR = {2004}
}


@INPROCEEDINGS{NK04d,
  AUTHOR = {Siegfried Nijssen and Joost N. Kok},
  TITLE = {The Gaston tool for Frequent Subgraph Mining},
  BOOKTITLE = {Proceedings of the International Workshop on Graph-Based Tools, Grabats 2004, Rome, Italy, October 2, 2004},
  PUBLISHER = {Elsevier},
  ABSTRACT = {Given a database of graphs, structure mining algorithms search for all substructures that satisfy constraints such as minimum frequency, minimum confidence, minimum interest and maximum frequency. In order to make frequent subgraph mining more efficient, we propose to search with steps of increasing complexity. We present the GrAph/Sequence/Tree extractiON ({\sc Gaston}) tool that implements this idea by searching first for frequent paths, then frequent free trees and finally cyclic graphs. We give results on large molecular databases.},
  YEAR = {2004}
}


@INPROCEEDINGS{Isra04b,
  AUTHOR = {M. Israel and E.L. van den Broek and P. van der Putten
and M.J. den Uyl},
  TITLE = {Real time automatic scene classification},
  BOOKTITLE = {Demonstration Paper at BNAIC'04},
  YEAR = {2004},
  ADDRESS = {Groningen, The Netherlands},
  CONFDATE = {Oct 21-22, 2004}
}


@ARTICLE{Putt04b,
  AUTHOR = {P. van der Putten and M. van Someren},
  TITLE = {A Bias-Variance Analysis of a Real World Learning
Problem: The CoIL Challenge 2000},
  JOURNAL = {Machine Learning},
  YEAR = {2004},
  MONTH = {October-- November},
  VOLUME = {57},
  ISSUE = {1--2},
  PAGES = {177-195}
}


@INPROCEEDINGS{Isra04a,
  AUTHOR = {M. Isra\"el and E. L. van den Broek and P. van der Putten
and M.J. den Uyl},
  TITLE = {Automating the Construction of scene classifiers for
Content-Based Video Retrieval},
  BOOKTITLE = {Proceedings of the Fifth International Workshop on
Multimedia DataMining (MDM/KDD'04)},
  YEAR = {2004},
  EDITOR = {L. Khan and V. A. Petrushin},
  PAGES = {38--47},
  ADDRESS = {Seattle, WA, USA},
  CONFDATE = {August 22, 2004}
}


@INPROCEEDINGS{Putt04a,
  AUTHOR = {P. van der Putten and A. Koudijs and R. Walker},
  TITLE = {Basel II Compliant Credit Risk Management: the OMEGA
Case},
  BOOKTITLE = {2nd EUNITE Workshop on Smart Adaptive Systems in Finance:
Intelligent Risk Analysis and Management},
  YEAR = {2004},
  ADDRESS = {Rotterdam, The Netherlands},
  CONFDATE = {May 19, 2004}
}


@ARTICLE{weko2004,
  AUTHOR = {M.C. van Wezel and W.A. Kosters},
  TITLE = {Nonmetric Multidimensional Scaling: Neural Networks Versus Traditional Techniques},
  YEAR = {2004},
  JOURNAL = {Intelligent Data Analysis},
  VOLUME = {8},
  PAGES = {601--613}
}


@INPROCEEDINGS{bako2004,
  AUTHOR = {K.J. Batenburg and W.A. Kosters},
  TITLE = {A Discrete Tomography Approach to Japanese Puzzles},
  BOOKTITLE = {Proceedings of BNAIC 2004, Groningen, The Netherlands},
  YEAR = {2004},
  MONTH = OCT,
  EDITOR = {R. Verbrugge and N. Taatgen and L. Schomaker},
  PAGES = {243--250}
}


@ARTICLE{prurope2004,
  AUTHOR = {M. Prudencio and J. Rohovec and J. A. Peters and E. Tocheva and M. J. Boulanger and M. E. P. Murphy and H. J. Hupkes and W.A.
   Kosters and A. Impagliazzo and M. Ubbink},
  TITLE = {A caged lanthanide complex as paramagnetic shift agent for protein NMR},
  JOURNAL = {Chemistry - A European Journal},
  VOLUME = {10},
  YEAR = {2004},
  PAGES = {3252-3260}
}