numerical mathematics, hierarchical matrices (H-matrices) are used as data-sparse approximations of non-sparse matrices. While a sparse matrix of dimension n...

A hierarchical organization or hierarchical organisation (see spelling differences) is an organizational structure where every entity in the organization...

function of many variables Hierarchical matrix, a data-sparse approximation of a non-sparse matrix Hilbert matrix, a square matrix with entries being the...

statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis that seeks to build a hierarchy of clusters...

curse in three steps: Hierarchical Clustering: Assets are grouped into clusters based on their correlations, forming a hierarchical tree structure. Quasi-Diagonalization:...

organization. The different types of organization charts include: Hierarchical Matrix Flat (also known as Horizontal) There is no accepted form for making...

culture management and matrix management, amongst others. None of these however has left behind the core tenets of Bureaucracy. Hierarchies still exist, authority...

published "Some hierarchical models for automatic document retrieval" in 1963 which also included a visual depiction of a document-term matrix. Salton was...

mathematics, computer science and especially graph theory, a distance matrix is a square matrix (two-dimensional array) containing the distances, taken pairwise...

matrices used in mathematics, science and engineering. A matrix (plural matrices, or less commonly matrixes) is a rectangular array of numbers called entries...

A risk matrix is a matrix that is used during risk assessment to define the level of risk by considering the category of likelihood (often confused with...

matrix is represented as a sequential matrix of rows and the requirement is to access a single column of the matrix. Efficiency of memory hierarchy use:...

marketing hierarchy, an engineering-oriented company produced "many ground-breaking computer systems." This is an example of cross-functional matrix management...

proof of stability. Hierarchical recurrent neural networks (HRNN) connect their neurons in various ways to decompose hierarchical behavior into useful...

Cooley–Tukey FFT algorithm was originally designed for systems with hierarchical memory common in modern computers (and was the first FFT algorithm in...

Bauer integrated matrix and discrete systems into USQ, or Universal SQ. It was a hierarchical 4-4-4 discrete matrix that used the SQ matrix as the baseband...

Nonlinear mixed-effects model Bayesian hierarchical modeling Restricted randomization also known as hierarchical linear models, linear mixed-effect models...

in terms of a hierarchical matrix approximation (HODLR) or basis function expansion (LatticeKrig, MRA, wavelets). The hierarchical matrix approach can...

resin or thermoplastics as a binder Ceramic matrix composites (composite ceramic and metal matrices) Metal matrix composites advanced composite materials...

in military intelligence, for uncovering insurgent networks of both hierarchical and leaderless nature.[citation needed] With the recent explosion of...

classifier Naive Bayes classifier Binary classifier Linear classifier Hierarchical classifier Dimensionality reduction Canonical correlation analysis (CCA)...

of the similarity matrix of the data to perform dimensionality reduction before clustering in fewer dimensions. The similarity matrix is provided as an...

hierarchical models there is no relationship between the size of the network and its average clustering coefficient. The development of hierarchical network...

in according quadrants in an Eisenhower matrix (also known as an Eisenhower box or Eisenhower decision matrix"). Tasks in the quadrants are then handled...

a fibre composite material, built as a series of hierarchical levels. At each level of the hierarchy, the collagen units are bound together by either...

of the original decisions such as the border points, and produces a hierarchical instead of a flat result. In 1972, Robert F. Ling published a closely...

linearly scaling fast weight controller (1992) learns to compute a weight matrix for further processing depending on the input. One of its two networks has...

The Hierarchical navigable small world (HNSW) algorithm is a graph-based approximate nearest neighbor search technique used in many vector databases. Nearest...

inverse of the covariance matrix. Hierarchical: algorithms which approximate the covariance matrix with a hierarchical matrix. These columns are about...

include neural networks, dimensionality reduction on the word co-occurrence matrix, probabilistic models, explainable knowledge base method, and explicit representation...