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  2. Gram matrix - Wikipedia

    en.wikipedia.org/wiki/Gram_matrix

    The Gram matrix of any orthonormal basis is the identity matrix. Equivalently, the Gram matrix of the rows or the columns of a real rotation matrix is the identity matrix. Likewise, the Gram matrix of the rows or columns of a unitary matrix is the identity matrix. The rank of the Gram matrix of vectors in or equals the dimension of the space ...

  3. Weighing matrix - Wikipedia

    en.wikipedia.org/wiki/Weighing_matrix

    (B) (,) of weight = and minimal order exist if is a prime power and such a circulant weighing matrix can be obtained by signing the complement of a finite projective plane. Since all C W ( n , k ) {\displaystyle CW(n,k)} for k ≤ 25 {\displaystyle k\leq 25} have been classified, the first open case is C W ( 105 , 36 ) {\displaystyle CW(105,36)} .

  4. Matrix (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Matrix_(mathematics)

    For example, if A is a 3-by-0 matrix and B is a 0-by-3 matrix, then AB is the 3-by-3 zero matrix corresponding to the null map from a 3-dimensional space V to itself, while BA is a 0-by-0 matrix. There is no common notation for empty matrices, but most computer algebra systems allow creating and computing with them.

  5. Low-rank matrix approximations - Wikipedia

    en.wikipedia.org/wiki/Low-rank_matrix_approximations

    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.

  6. Kernel embedding of distributions - Wikipedia

    en.wikipedia.org/wiki/Kernel_embedding_of...

    so is a Gram matrix over the distributions from which the training data are sampled. Finding an orthogonal transform onto a low-dimensional subspace B (in the feature space) which minimizes the distributional variance, DICA simultaneously ensures that B aligns with the bases of a central subspace C for which Y {\displaystyle Y} becomes ...

  7. Harris–Benedict equation - Wikipedia

    en.wikipedia.org/wiki/Harris–Benedict_equation

    The Harris–Benedict equation (also called the Harris-Benedict principle) is a method used to estimate an individual's basal metabolic rate (BMR).. The estimated BMR value may be multiplied by a number that corresponds to the individual's activity level; the resulting number is the approximate daily kilocalorie intake to maintain current body weight.

  8. Euclidean distance matrix - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance_matrix

    The Gram matrix of a sequence of points ,, …, in k-dimensional space ℝ k is the n×n matrix = of their dot products (here a point is thought of as a vector from 0 to that point): g i j = x i ⋅ x j = ‖ x i ‖ ‖ x j ‖ cos ⁡ θ {\displaystyle g_{ij}=x_{i}\cdot x_{j}=\|x_{i}\|\|x_{j}\|\cos \theta } , where θ {\displaystyle \theta ...

  9. One-repetition maximum - Wikipedia

    en.wikipedia.org/wiki/One-repetition_maximum

    One repetition maximum can also be used as an upper limit, in order to determine the desired "load" for an exercise (as a percentage of the 1RM). Weight training protocols often use 1RM when programming to ensure the exerciser reaches resistance overload, especially when the exercise objective is muscular strength, endurance or hypertrophy.