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People: Krisztian Buza, Dipl.-Ing.
Office hour:
C38 Spl, upon request
Phone, Fax, Email:
Phone: +49 5121/ 883-857
Fax: +49 5121 / 883-859
e-mail:
Postal address:
Information Systems and Machine Learning Lab
Marienburger Platz 22
University of Hildesheim
31141 Hildesheim
Germany
Visitor address:
Information Systems and Machine Learning Lab
Samelsonplatz 1
University of Hildesheim
31141 Hildesheim
Germany

Publications:
Books:

  • Krisztian Buza (2011):
    Fusion Methods for Time Series Classification, PhD thesis, University of Hildesheim, to appear as book at Peter Lang Verlag. PDF
Articles:
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme, Julia Koller (2011):
    Fast Classification of Electrocardiograph Signals via Instance Selection, in Proceedings of the First IEEE conference on Healthcare Informatics, Imaging and Systems Biology. PDF
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    INSIGHT: Efficient and Effective Instance Selection for Time-Series Classification, to appear in Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), LNCS Vol. 6635, Springer. PDF
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Fusion of Similarity Measures for Time-Series Classification, to appear in Proceedings of the 6th International Conference on Hybrid Artificial Intelligence Systems (HAIS), LNCS Vol. 6679, Springer. PDF
  • Krisztian Buza, Alexandros Nanopoulos, Tomáš Horváth, Lars Schmidt-Thieme (2011):
    GRAMOFON: General Model-selection Framework based on Networks, to appear in Neurocomputing, Elsevier .
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    IQ Estimation for Accurate Time-Series Classification, in IEEE Symposium Series on Computational Intelligence (SSCI) - IEEE Symposium on Computational Intelligence and Data Mining (CIDM). PDF
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2011):
    Individualized Error Estimation for Classification and Regression Models, in 34nd Annual Conference of the Gesellschaft für Klassifikation (GfKl 2010). PDF
  • Timo Reuter, Philipp Cimiano, Lucas Drumond, Krisztian Buza, Lars Schmidt-Thieme (2011):
    Scalable event-based clustering of social media via record linkage techniques, in Fifth International AAAI Conference on Weblogs and Social Media. PDF
  • Sebastian Blohm, Krisztian Buza, Philipp Cimiano, Lars Schmidt-Thieme (2011):
    Relation Extraction for the Semantic Web with Taxonomic Sequential Patterns, to appear in Applied Semantic Web Technologies.
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2010):
    Time-Series Classification based on Individualised Error Prediction, in 13th IEEE International Conference on Computational Science and Engineering (CSE-2010). Best paper award. PDF
  • Krisztian Buza, Alexandros Nanopoulos, Lars Schmidt-Thieme (2010):
    Graph-Based Model-Selection Framework for Large Ensembles, in 5th International Conference on Hybrid Artificial Intelligence Systems, HAIS2010, LNCS/LNAI 6076, pp. 559-566, Springer, Berlin/Heidelberg. PDF
  • Krisztian Buza (2010):
    Az AIDS elorehaladasanak felismerese gepi tanulas eszkozeivel (Prediction of HIV-progression using machine learning algorithms), in Internation Scientific Conference Series in Honour of the Hungarian Science Day at the College of Dunaujvaros. PDF
  • Krisztian Buza, Lars Schmidt-Thieme (2009):
    A Simple Ensemble Technique, in Analytic Challenge 'Ensembling' at the Australian Data Mining Conference (AusDM 2009). PDF
  • Krisztian Buza, Christine Preisach, Andre Busche, Lars Schmidt-Thieme, Wye Houn Leong, Mark Walters (2009):
    Eigenmode Identification in Campbell Diagrams, in International Workshop on Machine Learning for Aerospace. PDF
  • Lorenza Romano, Krisztian Buza, Claudio Giuliano, Lars Schmidt-Thieme (2009):
    XMedia: Web People Search by Clustering with Machinely Learned Similarity Measures, in 2nd Web People Search Evaluation Workshop at World Wide Web Conference. PDF
  • Krisztian Buza, Lars Schmidt-Thieme (2009):
    Motif-based Classification of Time Series with Bayesian Networks and SVMs, in Proceedings of 32nd Annual Conference of the Gesellschaft für Klassifikation (GfKl 2008). PDF
  • Krisztian Buza, Leandro Balby Marinho, Lars Schmidt-Thieme (2008):
    On Learning Knowledge Bases for Collabularies, in Internation Scientific Conference Series in Honour of the Hungarian Science Day at the College of Dunaujvaros. PDF
  • Leandro Balby Marinho, Krisztian Buza, Lars Schmidt-Thieme (2008):
    Folksonomy-based Collabulary Learning, in Proceedings of the International Semantic Web Conference (ISWC'08), Springer. PDF
  • Krisztian Buza, Ferenc Bodon (2007):
    Is it worth mining association rules?, in The 5th Hungarian-Japanese Symposium on Discrete Mathematics and Its Applications.
  • K. Buza, A. Buza, P. B. Kis (2010):
    Towards Better Modeling of Supermarkets, in IEEE International Joint Conferences on Computational Cybernetics and Technical Informatics (ICCC-CONTI 2010), Timisoara, Romania, pp. 499-503. PDF