Multiple kernel learning by conditional entropy minimization

Hideitsu Hino, Nima Reyhani, Noboru Murata

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    6 Citations (Scopus)

    Abstract

    Kernel methods have been successfully used in many practical machine learning problems. Choosing a suitable kernel is left to the practitioner. A common way to an automatic selection of optimal kernels is to learn a linear combination of element kernels. In this paper, a novel framework of multiple kernel learning is proposed based on conditional entropy minimization criterion. For the proposed framework, three multiple kernel learning algorithms are derived. The algorithms are experimentally shown to be comparable to or outperform kernel Fisher discriminant analysis and other multiple kernel learning algorithms on benchmark data sets.

    Original languageEnglish
    Title of host publicationProceedings - 9th International Conference on Machine Learning and Applications, ICMLA 2010
    Pages223-228
    Number of pages6
    DOIs
    Publication statusPublished - 2010
    Event9th International Conference on Machine Learning and Applications, ICMLA 2010 - Washington, DC
    Duration: 2010 Dec 122010 Dec 14

    Other

    Other9th International Conference on Machine Learning and Applications, ICMLA 2010
    CityWashington, DC
    Period10/12/1210/12/14

    Fingerprint

    Learning algorithms
    Entropy
    Discriminant analysis
    Learning systems

    Keywords

    • Discriminant analysis
    • Entropy
    • Kernel methods
    • Multiple Kernel Learning

    ASJC Scopus subject areas

    • Computer Science Applications
    • Human-Computer Interaction

    Cite this

    Hino, H., Reyhani, N., & Murata, N. (2010). Multiple kernel learning by conditional entropy minimization. In Proceedings - 9th International Conference on Machine Learning and Applications, ICMLA 2010 (pp. 223-228). [5708837] https://doi.org/10.1109/ICMLA.2010.40

    Multiple kernel learning by conditional entropy minimization. / Hino, Hideitsu; Reyhani, Nima; Murata, Noboru.

    Proceedings - 9th International Conference on Machine Learning and Applications, ICMLA 2010. 2010. p. 223-228 5708837.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Hino, H, Reyhani, N & Murata, N 2010, Multiple kernel learning by conditional entropy minimization. in Proceedings - 9th International Conference on Machine Learning and Applications, ICMLA 2010., 5708837, pp. 223-228, 9th International Conference on Machine Learning and Applications, ICMLA 2010, Washington, DC, 10/12/12. https://doi.org/10.1109/ICMLA.2010.40
    Hino H, Reyhani N, Murata N. Multiple kernel learning by conditional entropy minimization. In Proceedings - 9th International Conference on Machine Learning and Applications, ICMLA 2010. 2010. p. 223-228. 5708837 https://doi.org/10.1109/ICMLA.2010.40
    Hino, Hideitsu ; Reyhani, Nima ; Murata, Noboru. / Multiple kernel learning by conditional entropy minimization. Proceedings - 9th International Conference on Machine Learning and Applications, ICMLA 2010. 2010. pp. 223-228
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