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Nonlinear regression without i.i.d.assumption
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作者 Qing Xu xiaohua(michael)xuan 《Probability, Uncertainty and Quantitative Risk》 2019年第1期118-132,共15页
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 ... 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. 展开更多
关键词 Nonlinear regression MINIMAX INDEPENDENT Identically distributed Least squares Machine learning Quadratic programming
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