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» The Structure of Sparse Resultant Matrices
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SIAMSC
2008
132views more  SIAMSC 2008»
13 years 8 months ago
Stochastic Preconditioning for Diagonally Dominant Matrices
Abstract. This paper presents a new stochastic preconditioning approach for large sparse matrices. For the class of matrices that are row-wise and column-wise irreducibly diagonall...
Haifeng Qian, Sachin S. Sapatnekar
CORR
2010
Springer
134views Education» more  CORR 2010»
13 years 7 months ago
The LASSO risk for gaussian matrices
We consider the problem of learning a coefficient vector x0 ∈ RN from noisy linear observation y = Ax0 + w ∈ Rn . In many contexts (ranging from model selection to image proce...
Mohsen Bayati, Andrea Montanari
ICCV
2005
IEEE
14 years 10 months ago
Is Levenberg-Marquardt the Most Efficient Optimization Algorithm for Implementing Bundle Adjustment?
In order to obtain optimal 3D structure and viewing parameter estimates, bundle adjustment is often used as the last step of feature-based structure and motion estimation algorith...
Manolis I. A. Lourakis, Antonis A. Argyros
CSR
2008
Springer
13 years 10 months ago
Additive Preconditioning for Matrix Computations
Versus the customary preconditioners, our weakly random ones are generated more readily and for a much larger class of input matrices. Furthermore our preconditioners have a wider...
Victor Y. Pan, Dmitriy Ivolgin, Brian Murphy, Rhys...
AMC
2006
80views more  AMC 2006»
13 years 8 months ago
Parallel preconditioned conjugate gradient optimization of the Rayleigh quotient for the solution of sparse eigenproblems
A parallel algorithm based on the multidimensional minimization of the Rayleigh quotient is proposed to evaluate the leftmost eigenpairs of the generalized symmetric positive defi...
Luca Bergamaschi, Angeles Martinez, Giorgio Pini