Data Dependent Kernel Approximation using Pseudo Random Fourier Features

27 Nov 2017Bharath Bhushan DamodaranNicolas CourtyPhilippe-Henri Gosselin

Kernel methods are powerful and flexible approach to solve many problems in machine learning. Due to the pairwise evaluations in kernel methods, the complexity of kernel computation grows as the data size increases; thus the applicability of kernel methods is limited for large scale datasets... (read more)

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