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Jaakko Hollmén: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Artur Bykowski, Jouni K. Seppänen, Jaakko Hollmén
    Model-Independent Bounding of the Supports of Boolean Formulae in Binary Data. [Citation Graph (0, 0)][DBLP]
    Database Support for Data Mining Applications, 2004, pp:234-249 [Conf]
  2. Antti Rasinen, Jaakko Hollmén, Heikki Mannila
    Analysis of Linux Evolution Using Aligned Source Code Segments. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 2006, pp:209-218 [Conf]
  3. Salla Ruosaari, Jaakko Hollmén
    Image Analysis for Detecting Faulty Spots from Microarray Images. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 2002, pp:259-266 [Conf]
  4. Juha Vesanto, Jaakko Hollmén
    An Automated Report Generation Tool for the Data Understanding Phase. [Citation Graph (0, 0)][DBLP]
    HIS, 2001, pp:611-625 [Conf]
  5. Mika Sulkava, Pasi Rautio, Jaakko Hollmén
    Combining Measurement Quality into Monitoring Trends in Foliar Nutrient Concentrations. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2005, pp:761-767 [Conf]
  6. Jarkko Tikka, Amaury Lendasse, Jaakko Hollmén
    Analysis of Fast Input Selection: Application in Time Series Prediction. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2006, pp:161-170 [Conf]
  7. Michal Skubacz, Jaakko Hollmén
    Quantization of Continuous Input Variables for Binary Classification. [Citation Graph (0, 0)][DBLP]
    IDEAL, 2000, pp:42-47 [Conf]
  8. Peddinti V. Gopalacharyulu, Erno Lindfors, Catherine Bounsaythip, Teemu Kivioja, Laxman Yetukuri, Jaakko Hollmén, Matej Oresic
    Data integration and visualization system for enabling conceptual biology. [Citation Graph (0, 0)][DBLP]
    ISMB (Supplement of Bioinformatics), 2005, pp:177-185 [Conf]
  9. Jarkko Tikka, Jaakko Hollmén, Amaury Lendasse
    Input Selection for Long-Term Prediction of Time Series. [Citation Graph (0, 0)][DBLP]
    IWANN, 2005, pp:1002-1009 [Conf]
  10. Artur Bykowski, Jouni K. Seppänen, Jaakko Hollmén
    Model-independent Bounding of the Supports of Boolean Formulae in Binary Data. [Citation Graph (0, 0)][DBLP]
    KDID, 2002, pp:20-31 [Conf]
  11. Jaakko Hollmén, Volker Tresp
    Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:889-895 [Conf]
  12. Jaakko Hollmén, Jouni K. Seppänen, Heikki Mannila
    Mixture Models and Frequent Sets: Combining Global and Local Methods for 0-1 Data. [Citation Graph (0, 0)][DBLP]
    SDM, 2003, pp:- [Conf]
  13. Jaakko Hollmén
    Model Selection and Estimation Via Subjective User Preferences. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 2007, pp:259-263 [Conf]
  14. Jaakko Hollmén, Jarkko Tikka
    Compact and Understandable Descriptions of Mixtures of Bernoulli Distributions. [Citation Graph (0, 0)][DBLP]
    IDA, 2007, pp:1-12 [Conf]
  15. Jarkko Tikka, Jaakko Hollmén, Samuel Myllykangas
    Mixture Modeling of DNA Copy Number Amplification Patterns in Cancer. [Citation Graph (0, 0)][DBLP]
    IWANN, 2007, pp:972-979 [Conf]

  16. Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns. [Citation Graph (, )][DBLP]

  17. Selection of important input variables for RBF network using partial derivatives. [Citation Graph (, )][DBLP]

  18. Segmenting Multi-attribute Sequences Using Dynamic Bayesian Networks. [Citation Graph (, )][DBLP]

  19. Feature Extraction and Selection from Vibration Measurements for Structural Health Monitoring. [Citation Graph (, )][DBLP]

  20. Novelty Detection in Projected Spaces for Structural Health Monitoring. [Citation Graph (, )][DBLP]

  21. Preservation of Statistically Significant Patterns in Multiresolution 0-1 Data. [Citation Graph (, )][DBLP]

  22. Tracking your steps on the track: body sensor recordings of a controlled walking experiment. [Citation Graph (, )][DBLP]

  23. Benchmarking dynamic time warping for music retrieval. [Citation Graph (, )][DBLP]

  24. Spatio-temporal Road Condition Forecasting with Markov Chains and Artificial Neural Networks. [Citation Graph (, )][DBLP]

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