[UAI] JMLR: Special Issue on Kernel Methods

From: Nello Cristianini (nello@dcs.rhbnc.ac.uk)
Date: Fri Jan 05 2001 - 12:41:31 PST

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    CALL FOR PAPERS

    Journal of Machine Learning Research
    Special Issue on "New Perspectives on Kernel Based Learning Methods"
    http://www.cs.rhbnc.ac.uk/colt/JMLRspecissue.html

    Guest Editors:
    Nello Cristianini, John Shawe-Taylor, Bob Williamson

    Important dates:
    Submission deadline: March 15th, 2001
    Decision : May 15th, 2001
    Final Versions : June 15th, 2001

    Submission procedure:
    see webpage:
    http://www.cs.rhbnc.ac.uk/colt/JMLRspecissue.html

    Background:
    Recent theoretical advances and experimental results have drawn
    considerable attention to the use of kernel functions in learning systems.
    Support Vector Machines, Gaussian Processes, kernel PCA, kernel
    Gram-Schmidt, Bayes Point Machines, Relevance and Leverage Vector
    Machines, are just some of the algorithms that make crucial use of kernels
    for problems of classification, regression, density estimation, novelty
    detection and clustering.
    At the same time as these algorithms have been under development, novel
    techniques specifically designed for kernel-based systems have resulted in
    methods for assessing generalisation, implementing model selection, and
    analysing performance.
    The choice of model may be simply determined by parameters of the kernel,
    as for example the width of a Gaussian kernel. More recently, however,
    methods for designing and combining kernels have created a toolkit of
    options for choosing a kernel in a particular application.
    These methods have extended the applicability of the techniques beyond
    the natural Euclidean spaces to more general discrete structures. The
    field is witnessing growth on a number of fronts, with the publication of
    books, editing of special issues, organization of special sessions and
    web-sites.
    Moreover, a convergence of ideas and concepts from different disciplines
    is occurring.

    This special issue will accept papers in any of the following main
    research directions:

    1) design of novel kernel-based algorithms
    2) design of novel types of kernel functions
    3) development of new learning theory concepts
    4) application of the techniques to new problem areas

    More information at:
    http://www.cs.rhbnc.ac.uk/colt/JMLRspecissue.html

    Or: nello@dcs.rhbnc.ac.uk



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