,
Amir Shpilka
,
Ben Lee Volk
Creative Commons Attribution 4.0 International license
We give reconstruction algorithms for subclasses of depth-3 arithmetic circuits. In particular, we obtain the first efficient algorithm for finding tensor rank, and an optimal tensor decomposition as a sum of rank-one tensors, when given black-box access to a tensor of super-constant rank. Specifically, we obtain the following results:
1) A deterministic algorithm that reconstructs polynomials computed by Σ^{[k]}⋀^{[d]}Σ circuits in time poly(n,d,c) ⋅ poly(k)^{k^{k^{10}}},
2) A randomized algorithm that reconstructs polynomials computed by multilinear Σ^{[k]}∏^{[d]}Σ circuits in time poly(n,d,c) ⋅ k^{k^{k^{k^{O(k)}}}},
3) A randomized algorithm that reconstructs polynomials computed by set-multilinear Σ^{[k]}∏^{[d]}Σ circuits in time poly(n,d,c) ⋅ k^{k^{k^{k^{O(k)}}}},
where c = log q if 𝔽 = 𝔽_q is a finite field, and c equals the maximum bit complexity of any coefficient of f if 𝔽 is infinite.
Prior to our work, polynomial time algorithms for the case when the rank, k, is constant, were given by Bhargava, Saraf and Volkovich [Vishwas Bhargava et al., 2021].
Another contribution of this work is correcting an error from a paper of Karnin and Shpilka [Zohar Shay Karnin and Amir Shpilka, 2009] (with some loss in parameters) that also affected Theorem 1.6 of [Vishwas Bhargava et al., 2021]. Consequently, the results of [Zohar Shay Karnin and Amir Shpilka, 2009; Vishwas Bhargava et al., 2021] continue to hold, with a slightly worse setting of parameters. For fixing the error we systematically study the relation between syntactic and semantic notions of rank of Σ Π Σ circuits, and the corresponding partitions of such circuits.
We obtain our improved running time by introducing a technique for learning rank preserving coordinate-subspaces. Both [Zohar Shay Karnin and Amir Shpilka, 2009] and [Vishwas Bhargava et al., 2021] tried all choices of finding the "correct" coordinates, which, due to the size of the set, led to having a fast growing function of k at the exponent of n. We manage to find these spaces in time that is still growing fast with k, yet it is only a fixed polynomial in n.
@InProceedings{peleg_et_al:LIPIcs.ITCS.2024.87,
author = {Peleg, Shir and Shpilka, Amir and Volk, Ben Lee},
title = {{Tensor Reconstruction Beyond Constant Rank}},
booktitle = {15th Innovations in Theoretical Computer Science Conference (ITCS 2024)},
pages = {87:1--87:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-309-6},
ISSN = {1868-8969},
year = {2024},
volume = {287},
editor = {Guruswami, Venkatesan},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2024.87},
URN = {urn:nbn:de:0030-drops-196157},
doi = {10.4230/LIPIcs.ITCS.2024.87},
annote = {Keywords: Algebraic circuits, reconstruction, tensor decomposition, tensor rank}
}