Titlebook: Similarity Search and Applications; 16th International C Oscar Pedreira,Vladimir Estivill-Castro Conference proceedings 2023 The Editor(s)

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Shoshana Marcus,Dina Sokol,Sarah Zelikovitzd, the fractional form of Jacobi polynomials will be introduced, and the validation according to Mercer conditions will be proved. Finally, a comparison of the obtained results over a well-known dataset will be provided, using the mentioned kernels with some other orthogonal kernels as well as RBF a

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Edgar Chavez,Eric S. Tellezffusion, and wave. We used the modal Legendre functions, which have been introduced in Chap. . and have been applied several times in the previous chapters as the least squares support vector regression algorithm’s kernel basis in the presented method. The uniqueness of the obtained solution is prov

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Jaroslav Hlaváč,Martin Kopp,Jan Kohout,Tomá Skopalffusion, and wave. We used the modal Legendre functions, which have been introduced in Chap. . and have been applied several times in the previous chapters as the least squares support vector regression algorithm’s kernel basis in the presented method. The uniqueness of the obtained solution is prov

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Omar Shahbaz Khan,Martin Aumüller,Björn Þór Jónssond big data applications of support vector algorithms are growing. Consequently, the Compute Unified Device Architecture (CUDA) parallelizing the procedure of support vector algorithms based on orthogonal kernel functions is presented. The book sheds light on how to use support vector algorithms base

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