McKernel: A Library for Approximate Kernel Expansions in Log-linear Time
نویسندگان
چکیده
F2F is a C++ library for large-scale machine learning. It contains a CPU optimized implementation of the Fastfood algorithm in Le et al. (2013), 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 Transform (FWHT) that achieves compelling speed and outperforms current state-of-the-art methods has been developed. F2F allows to obtain non-linear classification combining Fastfood and a linear classifier.
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