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ICASSP
2011
IEEE
13 years 8 days ago
Basis Pursuit in sensor networks
Basis Pursuit (BP) finds a minimum ℓ1-norm vector z that satisfies the underdetermined linear system Mz = b, where the matrix M and vector b are given. Lately, BP has attracte...
João F. C. Mota, João M. F. Xavier, ...
NIPS
2008
13 years 10 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
GECCO
2005
Springer
195views Optimization» more  GECCO 2005»
14 years 2 months ago
Evolutionary strategies for multi-scale radial basis function kernels in support vector machines
In support vector machines (SVM), the kernel functions which compute dot product in feature space significantly affect the performance of classifiers. Each kernel function is suit...
Tanasanee Phienthrakul, Boonserm Kijsirikul
TSP
2008
106views more  TSP 2008»
13 years 8 months ago
Identification of Matrices Having a Sparse Representation
We consider the problem of recovering a matrix from its action on a known vector in the setting where the matrix can be represented efficiently in a known matrix dictionary. Conne...
Götz E. Pfander, Holger Rauhut, Jared Tanner
DAGM
2008
Springer
13 years 10 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