On Fast algorithms for orthogonal Tucker decomposition

We propose algorithms for Tucker tensor decomposition, which can avoid computing singular value decomposition or eigenvalue decomposition of large matrices as in the work-horse higher order orthogonal iteration (HOOI) algorithm. The novel algorithms require computational cost of O(I<sup>3</sup>R), which is cheaper than O(I<sup>3</sup>R + IR<sup>4</sup> + R<sup>6</sup>) of HOOI for multilinear rank-(R, R, R) tensors of size I × I × I.

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