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NIPS
2008
13 years 6 months ago
Theory of matching pursuit
We analyse matching pursuit for kernel principal components analysis (KPCA) by proving that the sparse subspace it produces is a sample compression scheme. We show that this bound...
Zakria Hussain, John Shawe-Taylor
PKDD
2009
Springer
147views Data Mining» more  PKDD 2009»
13 years 12 months ago
Kernel Polytope Faces Pursuit
Abstract. Polytope Faces Pursuit (PFP) is a greedy algorithm that approximates the sparse solutions recovered by 1 regularised least-squares (Lasso) [4,10] in a similar vein to (Or...
Tom Diethe, Zakria Hussain
DAGM
2008
Springer
13 years 7 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
ML
2002
ACM
146views Machine Learning» more  ML 2002»
13 years 5 months ago
Kernel Matching Pursuit
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
Pascal Vincent, Yoshua Bengio
ICASSP
2009
IEEE
14 years 3 days 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...