Norms of Random Submatrices and Sparse Approximation

Abstract

Many problems in the theory of sparse approximation require bounds on operator norms of a random submatrix drawn from a xed matrix. The purpose of this note is to collect estimates for several different norms that are most important in the analysis of `1 minimization algorithms. Several of these bounds have not appeared in detail.

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Document Details

Document Type
Technical Report
Publication Date
Jul 28, 2008
Accession Number
ADA633354

Entities

People

  • Joel A. Tropp

Organizations

  • California Institute of Technology

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Couplings
  • Harmonic Analysis
  • Hilbert Space
  • Inequalities
  • Information Operations
  • Mathematics
  • Probability
  • Random Variables
  • Sequences
  • Standards

Fields of Study

  • Computer science

Readers

  • Linear Algebra
  • Theoretical Analysis.