2017/08/08 by Erik Skau, Skau, Erik, Ágnes Szántó +1
Engineering · Mathematics · #14Q99 #15A69 #15A83 #Advanced Optimization Algorithms Research #Algebraic Geometry (math.AG) #FOS: Mathematics #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Tensor decomposition and applications
paper · pdf · doi:10.48550/arxiv.1708.02659
openalex publication_date 2017/08/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we examine a symmetric tensor decomposition problem, the Gramian decomposition, posed as a rank minimization problem. We study the relaxation of the problem and consider cases when the relaxed solution is a solution to the original problem. In some instances of tensor rank and order, we prove generically that the solution to the relaxation will be optimal in the original. In other cases, we present interesting examples and approaches that demonstrate the intricacy of this problem.