Approximability of p → q Matrix Norms: Generalized Krivine Rounding and Hypercontractive Hardness
Approximability of p → q Matrix Norms: Generalized Krivine Rounding and Hypercontractive Hardness
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DOI:
10.1137/1.9781611975482.83
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发表时间:
2019-01
影响因子:
2.1
通讯作者:
V. Bhattiprolu;Mrinalkanti Ghosh;V. Guruswami;Euiwoong Lee;Madhur Tulsiani
中科院分区:
文献类型:
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作者:
V. Bhattiprolu;Mrinalkanti Ghosh;V. Guruswami;Euiwoong Lee;Madhur Tulsiani
We study the problem of computing the p → q operator norm of a matrix A in R m × n , defined as || A || p → q := sup x ∈ R n \{ 0 } || Ax || q / || x || p . This problem generalizes the spectral norm of a matrix ( p = q = 2 ) and the Grothendieck problem ( p = ∞ , q = 1 ), and has been widely studied in various regimes. When p ≥ q , the problem exhibits a dichotomy: constant factor approximation algorithms are known if 2 is in [ q, p ] , and the problem is hard to approximate within almost polynomial factors when 2 is not in [q,p]. For the case when 2 is in [ q, p ] we prove almost matching approximation and NP-hardness results. The regime when p 2 was studied by [Barak et. al., STOC’12] who gave sub-exponential algorithms for a promise version of the problem (which captures small-set expansion) and also proved hardness of approximation results based on the Exponential Time Hypothesis. However, no NP-hardness of approximation is known for these problems for any p < q . We prove the first NP-hardness result for approximating hypercontractive norms. We show that for any 1 < p < q < ∞ with 2 not in [ p, q ] , || A || p → q is hard to approximate within 2 O (log 1 − ε n ) assuming NP is not contained in BPTIME(2 log O (1) n ) .