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A RANDOMIZED ALGORITHM FOR MULTIVARIATE FUNCTION APPROXIMATION

delete2017-01-01
delete16
PRE
AI
Y
Yeonjong Shin *
D
Dongbin Xiu
DOI:10.1137/16M1075193delete
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Abstract

Abstract

En 中文
The randomized Kaczmarz (RK) method is a randomized iterative algorithm for solving (overdetermined) linear systems of equations. In this paper, we extend the RK method to function approximation in a bounded domain. We demonstrate that by conducting the approximation randomly one sample at a time the method converges. Convergence analysis is conducted in terms of expectation, where we establish sharp upper and lower bounds for both the convergence rate of the algorithm and the error of the resulting approximation. The analysis also establishes the optimal sampling probability measure to achieve the optimal rate of convergence. Various numerical examples are provided to validate the theoretical results.
Keywords:
multivariate function approximation
Kaczmarz algorithm
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Journal

SIAM Journal on Scientific Computing cover
SIAM Journal on Scientific Computing
IF:
2.6
Papers:
5.1K
Citations:
1.8W

Organization

U
University System of Ohio
Scholars:
15.4W
Papers: 13.0W
Citations: 200