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TOMS
2008
120views more  TOMS 2008»
13 years 4 months ago
Families of algorithms related to the inversion of a Symmetric Positive Definite matrix
We present families of algorithms for operations related to the computation of the inverse of a Symmetric Positive Definite (SPD) matrix: Cholesky factorization, inversion of a tr...
Paolo Bientinesi, Brian C. Gunter, Robert A. van d...
CORR
2010
Springer
153views Education» more  CORR 2010»
13 years 4 months ago
Towards an Efficient Tile Matrix Inversion of Symmetric Positive Definite Matrices on Multicore Architectures
The algorithms in the current sequential numerical linear algebra libraries (e.g. LAPACK) do not parallelize well on multicore architectures. A new family of algorithms, the tile a...
Emmanuel Agullo, Henricus Bouwmeester, Jack Dongar...
MOC
2002
78views more  MOC 2002»
13 years 4 months ago
A geometric theory for preconditioned inverse iteration applied to a subspace
ABSTRACT. The aim of this paper is to provide a convergence analysis for a preconditioned subspace iteration, which is designated to determine a modest number of the smallest eigen...
Klaus Neymeyr
ICML
2002
IEEE
14 years 5 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
STOC
2007
ACM
128views Algorithms» more  STOC 2007»
14 years 5 months ago
Iteratively constructing preconditioners via the conjugate gradient method
We consider the problem of solving a symmetric, positive definite system of linear equations. The most well-known and widely-used method for solving such systems is the preconditi...
John Dunagan, Nicholas J. A. Harvey