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A sequential multilinear Nyström algorithm for streaming low-rank approximation of tensors in Tucker format (2407.03849v2)
Published 4 Jul 2024 in math.NA and cs.NA
Abstract: We present a sequential version of the multilinear Nystr\"om algorithm which is suitable for the low-rank Tucker approximation of tensors given in a streaming format. Accessing the tensor $\mathcal{A}$ exclusively through random sketches of the original data, the algorithm effectively leverages structures in $\mathcal{A}$, such as low-rankness, and linear combinations. We present a deterministic analysis of the algorithm and demonstrate its superior speed and efficiency in numerical experiments including an application in video processing.
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