Author:
Xu Qing,Xuan Xiaohua (Michael)
Abstract
Abstract
In this paper, we consider a class of nonlinear regression problems without the assumption of being independent and identically distributed. We propose a correspondent mini-max problem for nonlinear regression and give a numerical algorithm. Such an algorithm can be applied in regression and machine learning problems, and yields better results than traditional least squares and machine learning methods.
Publisher
American Institute of Mathematical Sciences (AIMS)
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