| |
Browse All Reviews > Mathematics Of Computing (G) > Numerical Analysis (G.1) > Numerical Linear Algebra (G.1.3) > Sparse, Structured, And Very Large Systems (Direct And Iterative Methods) (G.1.3...)
|
|
 |
|
|
| |
|
|
| |
1-10 of 46
Reviews about "Sparse, Structured, And Very Large Systems (Direct And Iterative Methods) (G.1.3...)":
|
Date Reviewed |
| |
Protein fold recognition based on sparse representation based classification
Yan K., Xu Y., Fang X., Zheng C., Liu B. Artificial Intelligence in Medicine 79 1-8, 2017. Type: Article
It is not reasonable to expect the sequence of amino acids to predict folding because many proteins with similar foldings have quite different sequences. To address this issue, this paper describes how sparse representation classificat...
|
Dec 18 2017 |
| |
 Sparse systems solving on GPUs with GMRES
Couturier R., Domas S. The Journal of Supercomputing 59(3): 1504-1516, 2012. Type: Article
In scientific computing, applications often rely heavily on solutions to linear systems. Thus, the efficiency of numerical methods for linear systems has great significance for applications. A generalized minimal residual method (GMRES...
|
Aug 14 2012 |
| |
Solving very sparse rational systems of equations
Cook W., Steffy D. ACM Transactions on Mathematical Software 37(4): 1-21, 2011. Type: Article
This paper does exactly what its title says, in the context of linear programming. It begins with an excellent review of the literature on the subject, and then considers four main techniques: Dixon’s p-adi...
|
Oct 26 2011 |
| |
CONTEST: a controllable test matrix toolbox for MATLAB
Taylor A., Higham D. ACM Transactions on Mathematical Software 35(4): 1-17, 2009. Type: Article
CONTEST is a toolbox for MATLAB that generates random networks. This paper describes its development. The toolbox is based on the implementation of nine models. The models produce directed graphs that can also be considered classes of ...
|
Sep 3 2010 |
| |
Exact and approximate sparse solutions of underdetermined linear equations
Jokar S., Pfetsch M. SIAM Journal on Scientific Computing 31(1): 23-44, 2008. Type: Article
This paper deals with the complexity and computation of sparse solutions of matrix equations. The matrix of interest has fewer rows than columns and is thus an underdetermined linear system. Of the multidimensional space of solutions, ...
|
Apr 20 2009 |
| |
Large-scale semidefinite programs in electronic structure calculation
Fukuda M., Braams B., Nakata M., Overton M., Percus J., Yamashita M., Zhao Z. Mathematical Programming: Series A 109(2): 553-580, 2007. Type: Article
The use of optimization techniques for solving electronic structure problems is dealt with in this paper. This is an excellent paper, and demonstrates the use of advanced methods in numerical optimization in state-of-the-art applicatio...
|
Nov 15 2007 |
| |
Algorithm 859: BABDCR--a Fortran 90 package for the solution of bordered ABD linear systems
Amodio P., Romanazzi G. ACM Transactions on Mathematical Software 32(4): 597-608, 2006. Type: Article
The solution of systems of linear algebraic equations Ax=f is discussed in this paper. It is assumed that matrix A is a bordered almost block diagonal (BABD) matrix....
|
Mar 16 2007 |
| |
An overview of SuperLU: algorithms, implementation, and user interface
Li X. ACM Transactions on Mathematical Software 31(3): 302-325, 2005. Type: Article
SuperLU is a package for solving large, sparse systems of linear equations using Gaussian elimination. It has versions for sequential machines (Sequential SuperLU), shared memory machines (SuperLU_MT), and distributed memory machines (...
|
Dec 16 2005 |
| |
Algorithm 844: Computing sparse reduced-rank approximations to sparse matrices
Berry M., Pulatova S., Stewart G. ACM Transactions on Mathematical Software 31(2): 252-269, 2005. Type: Article, Reviews: (2 of 2)
Reduced-rank approximations of sparse matrices lead to savings in both storage and computing time. Therefore, the use of such approximations is crucial in efforts to handle very large sparse matrices that arise in several fields of sci...
|
Oct 19 2005 |
| |
Algorithm 844: Computing sparse reduced-rank approximations to sparse matrices
Berry M., Pulatova S., Stewart G. ACM Transactions on Mathematical Software 31(2): 252-269, 2005. Type: Article, Reviews: (1 of 2)
Obtaining a sparse reduced-rank approximation for a large, sparse rectangular matrix is a problem that comes up in many application areas, one of which is latent semantic indexing. Therein, the objective is to compute a document vector...
|
Aug 23 2005 |
| |
|
|
| |
|
|
