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IDEAL
2010
Springer
13 years 4 months ago
Approximating the Covariance Matrix of GMMs with Low-Rank Perturbations
: Covariance matrices capture correlations that are invaluable in modeling real-life datasets. Using all d2 elements of the covariance (in d dimensions) is costly and could result ...
Malik Magdon-Ismail, Jonathan T. Purnell
TIT
2010
174views Education» more  TIT 2010»
13 years 1 months ago
Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
HYBRID
2004
Springer
14 years 9 days ago
Approximations of the Rate of Growth of Switched Linear Systems
The joint spectral radius of a set of matrices is a measure of the maximal asymptotic growth rate that can be obtained by forming long products of matrices taken from the set. This...
Vincent D. Blondel, Yurii Nesterov, Jacques Theys
AUTOMATICA
2011
12 years 10 months ago
A hierarchy of LMI inner approximations of the set of stable polynomials
Exploiting spectral properties of symmetric banded Toeplitz matrices, we describe simple sufficient conditions for positivity of a trigonometric polynomial formulated as linear ma...
Mustapha Ait Rami, Didier Henrion
CVPR
2010
IEEE
14 years 3 months ago
Fast Matting Using Large Kernel Matting Laplacian Matrices
Image matting is of great importance in both computer vision and graphics applications. Most existing state-of-the-art techniques rely on large sparse matrices such as the matting ...
Kaiming He, Jian Sun, Xiaoou Tang