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The Matrix Template Library (MTL) is a linear algebra library for C++ programs. The MTL uses template programming , which considerably reduces the code length. All matrices and vectors are available in all classical numerical formats: float , double , complex<float> or complex<double> .
The left null space of A is the same as the kernel of A T. The left null space of A is the orthogonal complement to the column space of A, and is dual to the cokernel of the associated linear transformation. The kernel, the row space, the column space, and the left null space of A are the four fundamental subspaces associated with the matrix A.
The Standard Library defines a specialization of the vector template for bool. The description of this specialization indicates that the implementation should pack the elements so that every bool only uses one bit of memory. [9] This is widely considered a mistake. [10] [11] vector<bool> does not meet the requirements for a C++ Standard Library ...
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Delayed evaluation solves this problem, and can be implemented in C++ by letting operator+ return an object of an auxiliary type, say VecSum, that represents the unevaluated sum of two Vecs, or a vector with a VecSum, etc. Larger expressions then effectively build expression trees that are evaluated only when assigned to an actual Vec variable ...
Armadillo is a C++ linear algebra library (matrix and vector maths), aiming towards a good balance between speed and ease of use. [1] It employs template classes, and has optional links to BLAS and LAPACK. The syntax is similar to MATLAB. Blitz++ is a high-performance vector mathematics library written in C++.
The estimator of the vector-valued regularization framework can also be derived from a Bayesian viewpoint using Gaussian process methods in the case of a finite dimensional Reproducing kernel Hilbert space. The derivation is similar to the scalar-valued case Bayesian interpretation of regularization.
The hyperplane learned in feature space by an SVM is an ellipse in the input space. In machine learning , the polynomial kernel is a kernel function commonly used with support vector machines (SVMs) and other kernelized models, that represents the similarity of vectors (training samples) in a feature space over polynomials of the original ...