Paper ID sheet UCL-INMA-2011.011
- Title
-
Jacobi algorithm for the best low multilinear rank approximation of symmetric tensors
- Authors
- Mariya Ishteva, P.-A. Absil, Paul Van Dooren
- Abstract
-
The problem discussed in this paper is the
symmetric best low multilinear rank approximation of third-order
symmetric tensors. We propose an algorithm based on Jacobi rotations,
for which symmetry is preserved at each iteration. Two numerical
examples are provided indicating the need of such algorithms. An
important part of the paper consists of proving that our algorithm
converges to stationary points of the objective function. This can be
considered an advantage of the proposed algorithm over existing
symmetry-preserving algorithms in the literature.
- Key words
- multilinear algebra; higher-order tensor; rank reduction; singular value decomposition; Jacobi rotation
- Status
- SIAM Journal on Matrix Analysis and Applications, 34(2), pp. 651-672, 2013
- Download
-
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