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ICASSP
2011
IEEE
14 years 3 months ago
Compressed sensing signal recovery via A* Orthogonal Matching Pursuit
Nazim Burak Karahanoglu, Hakan Erdogan
ICASSP
2011
IEEE
14 years 3 months ago
Subspace pursuit method for kernel-log-linear models
This paper presents a novel method for reducing the dimensionality of kernel spaces. Recently, to maintain the convexity of training, loglinear models without mixtures have been u...
Yotaro Kubo, Simon Wiesler, Ralf Schlüter, He...
TIT
2008
121views more  TIT 2008»
14 years 11 months ago
Stability Results for Random Sampling of Sparse Trigonometric Polynomials
Recently, it has been observed that a sparse trigonometric polynomial, i.e. having only a small number of non-zero coefficients, can be reconstructed exactly from a small number o...
Holger Rauhut
ECCV
2002
Springer
16 years 1 months ago
Robust Computer Vision through Kernel Density Estimation
Abstract. Two new techniques based on nonparametric estimation of probability densities are introduced which improve on the performance of equivalent robust methods currently emplo...
Haifeng Chen, Peter Meer
CORR
2008
Springer
186views Education» more  CORR 2008»
14 years 11 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