The Best Rank-One Approximation Ratio of a Tensor Space
In this paper we define the best rank-one approximation ratio of a tensor space. It turns out that in the finite dimensional case this provides an upper bound for the quotient of the residual of the best rank-one approximation of any tensor in that tensor space and the norm of that tensor. This uppe...
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| Veröffentlicht in: | SIAM journal on matrix analysis and applications Jg. 32; H. 2; S. 430 - 442 |
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| 1. Verfasser: | |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Philadelphia, PA
Society for Industrial and Applied Mathematics
01.04.2011
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| Schlagworte: | |
| ISSN: | 0895-4798, 1095-7162 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | In this paper we define the best rank-one approximation ratio of a tensor space. It turns out that in the finite dimensional case this provides an upper bound for the quotient of the residual of the best rank-one approximation of any tensor in that tensor space and the norm of that tensor. This upper bound is strictly less than one, and it gives a convergence rate for the greedy rank-one update algorithm. For finite dimensional general tensor spaces, third order finite dimensional symmetric tensor spaces, and finite biquadratic tensor spaces, we give positive lower bounds for the best rank-one approximation ratio. For finite symmetric tensor spaces and finite dimensional biquadratic tensor spaces, we give upper bounds for this ratio. [PUBLICATION ABSTRACT] |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0895-4798 1095-7162 |
| DOI: | 10.1137/100795802 |