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ICASSP
2009
IEEE
13 years 11 months ago
A low complexity Orthogonal Matching Pursuit for sparse signal approximation with shift-invariant dictionaries
We propose a variant of Orthogonal Matching Pursuit (OMP), called LoCOMP, for scalable sparse signal approximation. The algorithm is designed for shift-invariant signal dictionari...
Boris Mailhé, Rémi Gribonval, Fr&eac...
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...
CVPR
2005
IEEE
14 years 7 months ago
Infomax Boosting
In this paper, we described an efficient feature pursuit scheme for boosting. The proposed method is based on the infomax principle, which seeks optimal feature that achieves maxi...
Siwei Lyu
TSP
2008
70views more  TSP 2008»
13 years 4 months ago
Gradient Pursuits
Thomas Blumensath, Michael E. Davies
DAGM
2008
Springer
13 years 6 months ago
Example-Based Learning for Single-Image Super-Resolution
Abstract. This paper proposes a regression-based method for singleimage super-resolution. Kernel ridge regression (KRR) is used to estimate the high-frequency details of the underl...
Kwang In Kim, Younghee Kwon