Thursday, May 31, 2018

McKernel: A Library for Approximate Kernel Expansions in Log-linear Time - implementation -

Woohoo ! following up on a previous postJoachim lets me know of the release of an implementation:
Hi Igor,
The library is now up. The name changed to McKernel. Thanks for your interest.
Thanks !

Kernel Methods Next Generation (KMNG) introduces a framework to use kernel approximates in the mini-batch setting with SGD Optimizer as an alternative to Deep Learning. McKernel is a C++ library for KMNG ML Large-scale. It contains a CPU optimized implementation of the Fastfood algorithm that allows the computation of approximated kernel expansions in log-linear 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. McKernel allows to obtain non-linear classification combining Fastfood and a linear classifier.

Implementation is here:

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