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The Gram matrix is symmetric in the case the inner product is real-valued; it is Hermitian in the general, complex case by definition of an inner product. The Gram matrix is positive semidefinite, and every positive semidefinite matrix is the Gramian matrix for some set of vectors. The fact that the Gramian matrix is positive-semidefinite can ...
The energetic cost of running can be quantified through the measurement of oxygen consumption (VO2) during running at a given submaximal speed. During aerobic activities (like submaximal running), VO2 provides an indirect estimate of energy expenditure. [8]
Low-rank matrix approximations are essential tools in the application of kernel methods to large-scale learning problems. [ 1 ] Kernel methods (for instance, support vector machines or Gaussian processes [ 2 ] ) project data points into a high-dimensional or infinite-dimensional feature space and find the optimal splitting hyperplane.
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In multivariate statistics and probability theory, the scatter matrix is a statistic that is used to make estimates of the covariance matrix, for instance of the multivariate normal distribution. Definition
Partner sex may take a bit more energy, but you're still only burning around 4.2 calories a minute, according to a small study done by scientists at the University of Montreal in 2013.
In general, a distance matrix is a weighted adjacency matrix of some graph. In a network, a directed graph with weights assigned to the arcs, the distance between two nodes of the network can be defined as the minimum of the sums of the weights on the shortest paths joining the two nodes (where the number of steps in the path is bounded). [2]
In mathematics, a Euclidean distance matrix is an n×n matrix representing the spacing of a set of n points in Euclidean space.For points ,, …, in k-dimensional space ℝ k, the elements of their Euclidean distance matrix A are given by squares of distances between them.