REGULARIZED LEAST SQUARE REGRESSION WITH SPHERICAL POLYNOMIAL KERNELS

DOI10.1142/S0219691309003240zbMath1184.68410MaRDI QIDQ5189976

Luoqing Li

Publication date: 11 March 2010

Published in: International Journal of Wavelets, Multiresolution and Information Processing (Search for Journal in Brave)

zbMATH Keywords

reproducing kernel Hilbert spacelearning rateregularized least square regressionde la Vallée-Poussin operatorspherical polynomial kernel

Mathematics Subject Classification ID

General nonlinear regression (62J02) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (12)

LOCAL LEARNING ESTIMATES BY INTEGRAL OPERATORS ⋮ RANK-1 TENSOR PROJECTION VIA REGULARIZED REGRESSION FOR ACTION CLASSIFICATION ⋮ Nonparametric regression using needlet kernels for spherical data ⋮ The kernel regularized learning algorithm for solving Laplace equation with Dirichlet boundary ⋮ THE COEFFICIENT REGULARIZED REGRESSION WITH RANDOM PROJECTION ⋮ TEXTURE ANALYSIS USING GAUSSIAN GRAPHICAL MODELS ⋮ Learning rates of regularized regression on the unit sphere ⋮ Error analysis of kernel regularized pairwise learning with a strongly convex loss ⋮ GABOR-BASED TENSOR LOCAL DISCRIMINANT EMBEDDING AND ITS APPLICATION ON PALMPRINT RECOGNITION ⋮ Approximating and learning by Lipschitz kernel on the sphere ⋮ AN ASYMMETRIC ADAPTIVE CLASSIFICATION METHOD ⋮ MODEL SELECTION OF C-SUPPORT VECTOR MACHINES BASED ON MULTI-THREADING GENETIC ALGORITHM

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