Sketch Kernel Ridge Regression Using Circulant Matrix: Algorithm and Theory

Kernel ridge regression (KRR) is a powerful method for nonparametric regression. The time and space complexity of computing the KRR estimate directly are <inline-formula> <tex-math notation="LaTeX">\mathcal {O}(n^{3}) </tex-math></inline-formula> and <inline-form...

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Bibliographic Details
Published in:	IEEE transaction on neural networks and learning systems Vol. 31; no. 9; pp. 3512 - 3524
Main Authors:	Yin, Rong, Liu, Yong, Wang, Weiping, Meng, Dan
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.09.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Acceleration Algorithms Approximation Approximation algorithms Circulant matrix Complexity Convergence Fast Fourier transformations Fourier analysis Fourier transforms Kernel kernel ridge regression (KRR) Kernels large scale Mathematical analysis Matrix algebra Matrix methods Normal distribution random sketch Regression analysis Statistical analysis Theoretical analysis Time complexity Training
ISSN:	2162-237X, 2162-2388, 2162-2388
Online Access:	Get full text
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