In numerical analysis and scientific computing, a sparse matrix or sparse array is a matrix in which most of the elements are zero. There is no strict...

In mathematics, particularly matrix theory, a band matrix or banded matrix is a sparse matrix whose non-zero entries are confined to a diagonal band, comprising...

LAPACK defines various matrix representations in memory. There is also Sparse matrix representation and Morton-order matrix representation. According...

Sparse matrix–vector multiplication (SpMV) of the form y = Ax is a widely used computational kernel existing in many scientific applications. The input...

adjacency matrix and the time needed to perform operations on them is dependent on the matrix representation chosen for the underlying matrix. Sparse matrix representations...

following equivalent definition is in matrix form. Let V {\displaystyle V} be a p×p symmetric matrix, one can rewrite the sparse PCA problem as max T r ( Σ V )...

The Sparse Matrix Converter is an AC/AC converter which offers a reduced number of components, a low-complexity modulation scheme, and low realization...

directional gradient of a rasterized matrix. Once a matrix or a high dimensional vector is transferred to a sparse space, different recovery algorithms...

In linear algebra, a diagonal matrix is a matrix in which the entries outside the main diagonal are all zero; the term usually refers to square matrices...

Therefore, this type of data model relates to the mathematical notion of a sparse matrix. EAV is also known as object–attribute–value model, vertical database...

hierarchical matrices (H-matrices) are used as data-sparse approximations of non-sparse matrices. While a sparse matrix of dimension n {\displaystyle n} can be represented...

statistics, the projection matrix ( P ) {\displaystyle (\mathbf {P} )} , sometimes also called the influence matrix or hat matrix ( H ) {\displaystyle (\mathbf...

a hollow matrix may refer to one of several related classes of matrix: a sparse matrix; a matrix with a large block of zeroes; or a matrix with diagonal...

to BLAS for handling sparse matrices have been suggested over the course of the library's history; a small set of sparse matrix kernel routines was finally...

Charles E. (2009), "Parallel sparse matrix-vector and matrix-transpose-vector multiplication using compressed sparse blocks", ACM Symp. on Parallelism...

to the star height of a regular language. It has also found use in sparse matrix computations (see Bodlaender et al. 1995) and logic (Rossman 2008)....

each matrix column is equal to unity. The numerical coefficient α {\displaystyle \alpha } is known as a damping factor. Usually S is a sparse matrix and...

Adjustment of observations Stereoscopy Levenberg–Marquardt algorithm Sparse matrix Collinearity equation Structure from motion Simultaneous localization...

Non-negative matrix factorization (NMF or NNMF), also non-negative matrix approximation is a group of algorithms in multivariate analysis and linear algebra...

be sparse, that is, contain few nonzero entries. Therefore, specifically tailored matrix algorithms can be used in network theory. The Hessian matrix of...

indirect energy conversion by employing the Indirect Matrix Converter (Fig. 5) or the Sparse matrix converter which was invented by Prof. Johann W. Kolar...

or factorization factors a matrix as the product of a lower triangular matrix and an upper triangular matrix (see matrix decomposition). The product...

algorithm is the multiplication of matrix A {\displaystyle A} by a vector, so it is effective for a very large sparse matrix with appropriate implementation...

analysis, the entries of a matrix which change from zero to a non-zero value in the execution of an algorithm; see Sparse matrix#Reducing fill-in An issue...

Hierarchical matrix, a data-sparse approximation of a non-sparse matrix Hilbert matrix, a square matrix with entries being the unit fractions Hollow matrix, a square...

distance-based similarity. Algorithms to construct the graph adjacency matrix as a sparse matrix are typically based on a nearest neighbor search, which estimate...

multiple edges between two vertices P system – Computational model Sparse matrix–vector multiplication – Computation routine Petri Net – Model to describe...

document. For this reason, document-term matrices are usually stored in a sparse matrix format. As a result of the power-law distribution of tokens in nearly...

Regular matrix (disambiguation) Empty matrix Sparse matrix Paul E. Black, Ragged matrix, from Dictionary of Algorithms and Data Structures, Paul...

incomplete Cholesky factorization of a symmetric positive definite matrix is a sparse approximation of the Cholesky factorization. An incomplete Cholesky...