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    ICML
    2008
    IEEE
    177views Machine Learning» more  ICML 2008»
    Sparse multiscale gaussian process regression
    14 years 8 months ago
    Sparse multiscale gaussian process regression
    Download  eprints.pascal-network.org
    Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
    Bernhard Schölkopf, Christian Walder, Kwang I...
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    NIPS
    2008
    188views Information Technology» more  NIPS 2008»
    Bayesian Kernel Shaping for Learning Control
    13 years 9 months ago
    Bayesian Kernel Shaping for Learning Control
    Download  eprints.pascal-network.org
    In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
    Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakum...
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    ICML
    2008
    IEEE
    136views Machine Learning» more  ICML 2008»
    Training SVM with indefinite kernels
    14 years 8 months ago
    Training SVM with indefinite kernels
    Download  www.public.asu.edu
    Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
    Jianhui Chen, Jieping Ye
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    NA
    2008
    78views more  NA 2008»
    A walk through energy, discrepancy, numerical integration and group invariant measures on measurable subsets of euclidean space
    13 years 7 months ago
    A walk through energy, discrepancy, numerical integration and group invariant measures on measurable subsets of euclidean space
    Download  math.georgiasouthern.edu
    (A) The celebrated Gaussian quadrature formula on finite intervals tells us that the Gauss nodes are the zeros of the unique solution of an extremal problem. We announce recent re...
    S. B. Damelin
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    ICML
    2006
    IEEE
    167views Machine Learning» more  ICML 2006»
    On a theory of learning with similarity functions
    14 years 8 months ago
    On a theory of learning with similarity functions
    Download  www.cc.gatech.edu
    Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
    Maria-Florina Balcan, Avrim Blum
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