Symmetric Orthogonal Tensor Decomposition is Trivial

Abstract

We consider the problem of decomposing a real-valued symmetric tensor as the sum of outer products of real-valued, pairwise orthogonal vectors. Such decompositions do not generally exist, but we show that some symmetric tensor decomposition problems can be converted to orthogonal problems following the whitening procedure proposed by Anandkumar et al. (2012). If an orthogonal decomposition of an $m$-way $n$-dimensional symmetric tensor exists, we propose a novel method to compute it that reduces to an $n\times n$ symmetric matrix eigenproblem. We provide numerical results demonstrating the effectiveness of the method.

References in corpus (2)

• Numerical Optimization for Symmetric Tensor Decomposition
• Generating Polynomials and Symmetric Tensor Decompositions

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