DocumentCode :
2376774
Title :
Tensor Rank: Some Lower and Upper Bounds
Author :
Alexeev, Boris ; Forbes, Michael A. ; Tsimerman, Jacob
Author_Institution :
Dept. of Math., Princeton Univ., Princeton, NJ, USA
fYear :
2011
fDate :
8-11 June 2011
Firstpage :
283
Lastpage :
291
Abstract :
The results of Strassen and Raz show that good enough tensor rank lower bounds have implications for algebraic circuit/formula lower bounds. We explore tensor rank lower and upper bounds, focusing on explicit tensors. For odd d, we construct field-independent explicit 0/1 tensors T : [n]d → F with rank at least 2n⌊d/2⌋ + n - Θ(d lg n). This improves the lower-order terms in known lower bounds for any odd d ≥ 3. We also explore a generalization of permutation matrices, which we denote permutation tensors. We show, by apply ing known counting lower bounds, that there exist order-3 permutation tensors with super-linear rank as well as order d permutation tensors with high rank. We also explore a natural class of permutation tensors, which we call group tensors. For any group G, we define the group tensor TGd : Gd → F, by TGd(g1, ,gd) = 1 iff g1 ⋯ gd = 1G. We give two upper bounds for the rank of these tensors. The first uses representation theory and works over "large" fields F, showing (among other things) that rankF(TGd) ≤ |G|d/2. In the case that d = 3, we are able to show that rankF(TG3) ≤ O(|G|ω/2) ≤ O(|G|1.19), where ω is the exponent of matrix multiplication. The next upper bound uses interpolation and only works for abelian G, showing that over any field F that rankF(TGd) ≤ O(|G|1+1g d lgd-1 |G|). In either case, this shows that many permutation tensors have far from maximal rank, which is very different from the matrix case and thus eliminates many natural candidates for high tensor rank. We also explore monotone tensor rank. We give explicit 0/1 tensors T - - : [n]d → F that have tensor rank at most dn but have monotone tensor rank exactly nd-1. This is a nearly optimal separation.
Keywords :
circuit complexity; interpolation; matrix multiplication; tensors; algebraic circuit lower bound; algebraic formula lower bound; group tensor; interpolation; matrix multiplication; permutation matrices; permutation tensor; representation theory; tensor rank lower bounds; tensor rank upper bound; Complexity theory; Computational modeling; Integrated circuit modeling; Polynomials; Tensile stress; USA Councils; Upper bound; algebraic complexity; tensor rank;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Complexity (CCC), 2011 IEEE 26th Annual Conference on
Conference_Location :
San Jose, CA
ISSN :
1093-0159
Print_ISBN :
978-1-4577-0179-5
Electronic_ISBN :
1093-0159
Type :
conf
DOI :
10.1109/CCC.2011.28
Filename :
5959837
Link To Document :
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