Sparse Recovery, Kashin Decomposition and Conic Programming

Abstract

We produce relaxation bounds on the diameter of arbitrary sections of the l1 ball in R^n. We use these results to test conditions for sparse recovery.

First, conference version

References in corpus (1)

• On Low Rank Matrix Approximations with Applications to Synthesis Problem in Compressed Sensing

Cited by in corpus (3)

• High-dimensional genome-wide association study and misspecified mixed model analysis
• Compressed Sensing Recoverability In Imaging Modalities
• Boundary multifractal behaviour for harmonic functions in the ball