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ICASSP
2010
IEEE
13 years 5 months ago
Gradient Polytope Faces Pursuit for large scale sparse recovery problems
Polytope Faces Pursuit is a greedy algorithm that performs Basis Pursuit with similar order complexity to Orthogonal Matching Pursuit. The algorithm adds one basis vector at a tim...
Aris Gretsistas, Ivan Damnjanovic, Mark D. Plumble...
TSP
2010
12 years 11 months ago
Shifting inequality and recovery of sparse signals
Abstract--In this paper, we present a concise and coherent analysis of the constrained `1 minimization method for stable recovering of high-dimensional sparse signals both in the n...
T. Tony Cai, Lie Wang, Guangwu Xu
CORR
2012
Springer
201views Education» more  CORR 2012»
12 years 15 days ago
Signal Recovery on Incoherent Manifolds
Suppose that we observe noisy linear measurements of an unknown signal that can be modeled as the sum of two component signals, each of which arises from a nonlinear sub-manifold ...
Chinmay Hegde, Richard G. Baraniuk
CVPR
2012
IEEE
11 years 7 months ago
Bilevel sparse coding for coupled feature spaces
In this paper, we propose a bilevel sparse coding model for coupled feature spaces, where we aim to learn dictionaries for sparse modeling in both spaces while enforcing some desi...
Jianchao Yang, Zhaowen Wang, Zhe Lin, Xianbiao Shu...
CORR
2008
Springer
186views Education» more  CORR 2008»
13 years 4 months ago
Greedy Signal Recovery Review
The two major approaches to sparse recovery are L1-minimization and greedy methods. Recently, Needell and Vershynin developed Regularized Orthogonal Matching Pursuit (ROMP) that ha...
Deanna Needell, Joel A. Tropp, Roman Vershynin