Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method


We give a new approach to the dictionary learning (also known as "sparse coding") problem of recovering an unknown n x m matrix A (for m &#8805; n) from examples of the form [y = Ax + e,] where x is a random vector in R<sup>m</sup> with at most &#964; m nonzero coordinates, and e is a random noise vector in R<sup>n</sup> with bounded magnitude. For the case… (More)
DOI: 10.1145/2746539.2746605


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