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Extrapolated Alternating Algorithms For Approximate Canonical Polyadic Decomposition
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Extrapolated Alternating Algorithms For Approximate Canonical Polyadic Decomposition
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Tensor decompositions have become a central tool in machine learning to extract interpretable patterns from multiway arrays of data. However, computing the approximate Canonical Polyadic Decomposition (aCPD), one of the most important tensor decomposition
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