Nonlinear regression without i.i.d. assumption View Full Text


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Article Info

DATE

2019-11-05

AUTHORS

Qing Xu, Xiaohua (Michael) Xuan

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. More... »

PAGES

8

References to SciGraph publications

  • 1987-11. A direct method of linearization for continuous minimax problems in JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
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    http://scigraph.springernature.com/pub.10.1186/s41546-019-0042-6

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    http://dx.doi.org/10.1186/s41546-019-0042-6

    DIMENSIONS

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