Generating compact representations of high-dimensional data
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United States of America Patent
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Jan 16, 2018
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app pub date -
May 12, 2015
filing date -
May 12, 2015
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Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks with an external memory. One of the methods includes receiving a plurality of high-dimensional data items; generating a circulant embedding matrix for the high-dimensional data items, wherein the circulant embedding matrix is a matrix that is fully specified by a single vector; for each high-dimensional data item, generating a compact representation of the high-dimensional data item, comprising computing a product of the circulant embedding matrix and the high dimensional data item by performing a circular convolution of the single vector that fully specifies the circulant embedding matrix and the high dimensional data item using a Fast Fourier Transform (FFT); and generating a compact representation of the high dimensional data item by computing a binary map of the computed product.
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