Kai Puolamäki

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  1. An approximation ratio for biclustering

    Puolamäki, K., Hanhijarvi, S. & Garriga, G. C., 30 Sep 2008, In : Information Processing Letters. 108, 2, p. 45-49 5 p.

    Research output: Contribution to journalArticleScientificpeer-review

  2. Tell Me Something I Don't Know: Randomization Strategies for Iterative Data Mining

    Hanhijarvi, S., Ojala, M., Vuokko, N., Puolamäki, K., Tatti, N. & Mannila, H., 2009, Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining . New York: ASSOC COMPUTING MACHINERY, p. 379-387 9 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  3. Analyzing Word Frequencies in Large Text Corpora Using Inter-arrival Times and Bootstrapping

    Lijffijt, J., Papapetrou, P., Puolamäki, K. & Mannila, H., 2011, MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT II. Gunopulos, D., Hofmann, T., Malerba, D. & Vazirgiannis, M. (eds.). Springer-Verlag, p. 341-357 17 p. (Lecture Notes in Artificial Intelligence; vol. 6912).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  4. Sound Sample Detection and Numerosity Estimation Using Auditory Display

    Gamper, H., Dicke, C., Billinghurst, M. & Puolamäki, K., Feb 2013, In : ACM transactions on applied perception.. 10, 1, 18 p., 4.

    Research output: Contribution to journalArticleScientificpeer-review

  5. A statistical significance testing approach to mining the most informative set of patterns

    Lijffijt, J., Papapetrou, P. & Puolamaki, K., Jan 2014, In : Data Mining and Knowledge Discovery. 28, 1, p. 238-263 26 p.

    Research output: Contribution to journalArticleScientificpeer-review

  6. Confidence bands for time series data

    Korpela, J., Puolamaki, K. & Gionis, A., Sep 2014, In : Data Mining and Knowledge Discovery. 28, 5-6, p. 1530-1553 24 p.

    Research output: Contribution to journalArticleScientificpeer-review

  7. A peek into the black box: exploring classifiers by randomization

    Henelius, A., Puolamaki, K., Bostrom, H., Asker, L. & Papapetrou, P., Sep 2014, In : Data Mining and Knowledge Discovery. 28, 5-6, p. 1503-1529 27 p.

    Research output: Contribution to journalArticleScientificpeer-review

  8. GoldenEye plus plus: A Closer Look into the Black Box

    Henelius, A., Puolamaki, K., Karlsson, I., Zhao, J., Asker, L., Bostrom, H. & Papapetrou, P., 2015, STATISTICAL LEARNING AND DATA SCIENCES. Gammerman, A., Vovk & Papadopoulos, H. (eds.). Springer-Verlag, p. 96-105 10 p. (Lecture Notes in Artificial Intelligence; vol. 9047).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

  9. Size matters: choosing the most informative set of window lengths for mining patterns in event sequences

    Lijffijt, J., Papapetrou, P. & Puolamaki, K., Nov 2015, In : Data Mining and Knowledge Discovery. 29, 6, p. 1838-1864 27 p.

    Research output: Contribution to journalArticleScientificpeer-review

  10. A Tool for Subjective and Interactive Visual Data Exploration

    Kang, B., Puolamäki, K., Lijffijt, J. & De Bie, T., 2016, MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2016, PT III. Berendt, B., Bringmann, B., Fromont, E., Garriga, G., Miettinen, P., Tatti, N. & Tresp (eds.). Springer-Verlag, p. 3-7 5 p. (Lecture Notes in Artificial Intelligence; vol. 9853).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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