F2F: A Library For Fast Kernel Expansions

    Joachim Curto
    Joachim Curto
    Irene Zarza
    Irene Zarza
    Feng Yang
    Feng Yang

    arXiv: Learning, Volume abs/1702.08159, 2017.

    Cited by: 0|Bibtex|13|
    EI

    Abstract:

    F2F is a C++ library for large-scale machine learning. It contains a CPU optimized implementation of the Fastfood algorithm, that allows the computation of approximated kernel expansions in loglinear time. The algorithm requires to compute the product of Walsh-Hadamard Transform (WHT) matrices. A cache friendly SIMD Fast Walsh-Hadamard Tr...More
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