- Referenced in 74 articles
- package Matrix: Sparse and Dense Matrix Classes and Methods , Classes and methods for dense...
- Referenced in 79 articles
- large problems. It utilizes Matlab’s sparse-matrix data-structure and Application Program Interface facility ... existing, efficient Fortran codes for solving large, sparse, symmetric positive deﬁnite linear systems. Specifically, LIPSOL...
- Referenced in 90 articles
- Performs Penalized Multivariate Analysis: a penalized matrix decomposition, sparse principal components analysis, and sparse canonical ... Hastie (2009) A penalized matrix decomposition, with applications to sparse principal components and canonical correlation...
- Referenced in 54 articles
- following problems: Matrix Complete (MC), Sparse Matrix Separation (SMS), Matrix Compressive Sensing...
- Referenced in 44 articles
- package also contains an implementation of sparse matrix methods for large spatial data sets ... currently requires the sparse matrix (spam) package. But spam is not required for the standard...
- Referenced in 53 articles
- large matrices there is a special sparse-matrix class named ”Incomplete” that efficiently handles ... computing low-rank SVDs on large sparse centered matrices (i.e. principal components...
- Referenced in 45 articles
- based, normal flow, quasi-Newton augmented Jacobian matrix – are provided for tracking homotopy zero curves ... well as separate routines for dense and sparse Jacobian matrices. A high level driver ... games, support for several sparse matrix data structures, and new iterative algorithms for large sparse...
- Referenced in 47 articles
- parallel sparse linear solver. Watson Sparse Matrix Package (WSMP) is a collection of algorithms ... linear equations whose coefficient matrices are sparse. This high-performance, robust, and easy...
- Referenced in 33 articles
- iterative solution module for a parallel sparse matrix library (P-SPARSLIP) The authors develop ... portable FORTRAN routine for sparse matrix computation. It emphasizes iterative techniques...
- Referenced in 455 articles
- associated eigenvectors of a matrix A. The matrix can be real or complex, Hermitian ... effective especially in case A is sparse and of large size. The Jacobi-Davidson method...
- Referenced in 27 articles
- package spam: SPArse Matrix: Set of functions for sparse matrix algebra. Differences with SparseM/Matrix ... only support (essentially) one sparse matrix format, (2) based on transparent and simple structure...
- Referenced in 187 articles
- matrix A may be either full or sparse; computations are made accordingly. This...
- Referenced in 38 articles
- CUSP : A C++ Templated Sparse Matrix Library. Cusp is a library for sparse linear algebra...
- Referenced in 542 articles
- together with the associated eigenvectors of a matrix pencil A-lambda*B. The matrices ... especially in case A and B are sparse and of large size. The Jacobi-Davidson...
- Referenced in 35 articles
- format; Level 2: operations between a matrix in sparse format and a vector in dense ... format; Level 3: operations between a matrix in sparse format and a set of vectors ... usually be viewed as a dense tall matrix); Conversion: operations that allow conversion between different...
- Referenced in 39 articles
- Cholesky factorization based on the Yale Sparse Matrix Package. In this paper we briefly describe...
- Referenced in 112 articles
- itself may be dense, sparse, or factored) and a matrix along each mode...
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- derivatives, we may utilize MATLAB’s sparse matrix class to propagate sparse directional derivatives...
- Referenced in 35 articles
- decomposition of a covariance matrix into sparse factors, and has wide applications ranging from biology ... largest eigenvalue of a symmetric matrix, where cardinality is constrained, and derive a semidefinite programming ... arising in the direct sparse PCA method...
- Referenced in 13 articles
- Sparsity: Optimization Framework for Sparse Matrix Kernels. Sparse matrix–vector multiplication is an important computational ... zero structure of the matrix. The SPARSITY system is designed to address these problems ... allowing users to automatically build sparse matrix kernels that are tuned to their matrices ... optimization of two operations: a sparse matrix times a dense vector and a sparse matrix...