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Streaming Kernel PCA with ˜ O(√n) Random Features

2020-02-14 | |  43 |   42 |   0

Abstract 

We study the statistical and computational aspects of kernel principal component analysis ? using random Fourier features and show that under mild assumptions,image.png features suffice to achieve image.png sample complexity. Furthermore, we give a memory efficient streaming algorithm based on classical Oja’s algorithm that achieves this rate.

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