Reproducing Kernel Hilbert Space

アルゴリズム:Algorithms

Protected:  Sparse learning based on group L1 norm regularization

Sparse machine learning based on group L1-norm regularization for digital transformation, artificial intelligence, and machine learning tasks relative dual gap, dual problem, gradient descent, extended Lagrangian function, dual extended Lagrangian method, Hessian, L1-norm regularization, and group L1-norm regularization, dual norm, empirical error minimization problem, prox operator, Nesterov's acceleration method, proximity gradient method, iterative weighted reduction method, variational representation, nonzero group number, kernel weighted regularization term, concave conjugate, regenerative kernel Hilbert space, support vector machine, kernel weight Multi-kernel learning, basis kernel functions, EEG signals, MEG signals, voxels, electric dipoles, neurons, multi-task learning
アルゴリズム:Algorithms

Protected: Kernel functions as the basis of kernel methods in statistical mathematics theory.

Kernel functions (Gaussian kernels, polynomial kernels, linear kernels, kernel functions, regression functions, linear models, regression problems, discriminant problems) as the basis for kernel methods in statistical mathematics theory used in digital transformation, artificial intelligence and machine learning tasks.
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