1 Search Results for "Natarajan, Abhiram"

Document

DOI: 10.4230/LIPIcs.APPROX-RANDOM.2014.371

Computational Complexity of Certifying Restricted Isometry Property

Authors: Abhiram Natarajan and Yi Wu

Published in: LIPIcs, Volume 28, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014)

Abstract

Given a matrix A with n rows, a number k < n, and 0 < delta < 1, A is (k,delta)-RIP (Restricted Isometry Property) if, for any vector x in R^n, with at most k non-zero co-ordinates, (1-delta)|x|^2 <= |Ax|^2 <= (1+delta)|Ax|^2. In many applications, such as compressed sensing and sparse recovery, it is desirable to construct RIP matrices with a large k and a small delta;. Given the efficacy of random constructions in generating useful RIP matrices, the problem of certifying the RIP parameters of a matrix has become important. In this paper, we prove that it is hard to approximate the RIP parameters of a matrix assuming the Small-Set-Expansion-Hypothesis. Specifically, we prove that for any arbitrarily large constant C>0 and any arbitrarily small constant 0<delta<1, there exists some k such that given a matrix M, it is SSE-Hard to distinguish the following two cases: i) (Highly RIP) M is (k,delta)-RIP; ii) (Far away from RIP) M is not (k/C,1-delta)-RIP. Most of the previous results on the topic of hardness of RIP certification only hold for certification when delta=o(1). In practice, it is of interest to understand the complexity of certifying a matrix with delta being close to sqrt(2) - 1, as it suffices for many real applications to have matrices with delta=sqrt(2)-1. Our hardness result holds for any constant delta. Specifically, our result proves that even if delta is indeed very small, i.e. the matrix is in fact strongly RIP, certifying that the matrix exhibits weak RIP itself is SSE-Hard. In order to prove the hardness result, we prove a variant of the Cheeger's Inequality for sparse vectors.

Cite as

Abhiram Natarajan and Yi Wu. Computational Complexity of Certifying Restricted Isometry Property. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014). Leibniz International Proceedings in Informatics (LIPIcs), Volume 28, pp. 371-380, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

Copy BibTex To Clipboard

@InProceedings{natarajan_et_al:LIPIcs.APPROX-RANDOM.2014.371,
  author =	{Natarajan, Abhiram and Wu, Yi},
  title =	{{Computational Complexity of Certifying Restricted Isometry Property}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014)},
  pages =	{371--380},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-74-3},
  ISSN =	{1868-8969},
  year =	{2014},
  volume =	{28},
  editor =	{Jansen, Klaus and Rolim, Jos\'{e} and Devanur, Nikhil R. and Moore, Cristopher},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2014.371},
  URN =		{urn:nbn:de:0030-drops-47092},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2014.371},
  annote =	{Keywords: Restricted Isometry Property, RIP, RIP Certification, Sparse Cheeger Inequality, SSE Hard}
}

Refine by Author
1 Natarajan, Abhiram
1 Wu, Yi

Refine by Classification

Refine by Keyword
1 RIP
1 RIP Certification
1 Restricted Isometry Property
1 SSE Hard
1 Sparse Cheeger Inequality

Refine by Type
1 document

Refine by Publication Year
1 2014

1 Search Results for "Natarajan, Abhiram"

Computational Complexity of Certifying Restricted Isometry Property

Abstract

Cite as

Thanks for your feedback!

Could not send message