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» Some Elimination Problems for Matrices
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TNN
2010
148views Management» more  TNN 2010»
13 years 4 months ago
Generalized low-rank approximations of matrices revisited
Compared to Singular Value Decomposition (SVD), Generalized Low Rank Approximations of Matrices (GLRAM) can consume less computation time, obtain higher compression ratio, and yiel...
Jun Liu, Songcan Chen, Zhi-Hua Zhou, Xiaoyang Tan
SIAMMAX
2010
103views more  SIAMMAX 2010»
13 years 4 months ago
On Chebyshev Polynomials of Matrices
The mth Chebyshev polynomial of a square matrix A is the monic polynomial that minimizes the matrix 2-norm of p(A) over all monic polynomials p(z) of degree m. This polynomial is u...
Vance Faber, Jörg Liesen, Petr Tichý
CPHYSICS
2007
222views more  CPHYSICS 2007»
13 years 9 months ago
JADAMILU: a software code for computing selected eigenvalues of large sparse symmetric matrices
A new software code for computing selected eigenvalues and associated eigenvectors of a real symmetric matrix is described. The eigenvalues are either the smallest or those closes...
Matthias Bollhöfer, Yvan Notay
SIAMJO
2011
13 years 4 months ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
DGCI
2000
Springer
14 years 2 months ago
Reconstruction of Discrete Sets with Absorption
A generalization of a classical discrete tomography problem is considered: Reconstruct binary matrices from their absorbed row and columns sums, i.e., when some known absorption is...
Attila Kuba, Maurice Nivat