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Sigma-Delta and Distributed Noise-Shaping Quantization Methods for Random Fourier Features

By Jinjie Zhang and others
We propose the use of low bit-depth Sigma-Delta and distributed noise-shaping methods for quantizing the Random Fourier features (RFFs) associated with shift-invariant kernels. We prove that our quantized RFFs -- even in the case of 1-bit quantization -- allow a high accuracy approximation of the underlying kernels, and the approximation... Show more
April 13, 2022
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Sigma-Delta and Distributed Noise-Shaping Quantization Methods for Random Fourier Features
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