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pro vyhledávání: '"Yao, Qiuran"'
This paper studies the distribution estimation of contaminated data by the MoM-GAN method, which combines generative adversarial net (GAN) and median-of-mean (MoM) estimation. We use a deep neural network (DNN) with a ReLU activation function to mode
Externí odkaz:
http://arxiv.org/abs/2212.13741
The generative adversarial networks (GANs) have recently been applied to estimating the distribution of independent and identically distributed data, and have attracted a lot of research attention. In this paper, we use the blocking technique to demo
Externí odkaz:
http://arxiv.org/abs/2211.14577
There has been a surge of interest in developing robust estimators for models with heavy-tailed and bounded variance data in statistics and machine learning, while few works impose unbounded variance. This paper proposes two type of robust estimators
Externí odkaz:
http://arxiv.org/abs/2201.03182
Autor:
Yao, Qiuran1,2 (AUTHOR), Zhang, Huiming1,2 (AUTHOR) huimingzhang@um.edu.mo
Publikováno v:
Stat. Dec2022, Vol. 11 Issue 1, p1-10. 10p.
Akademický článek
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Autor:
Zhang, Qian1,2,3 (AUTHOR), Jiang, Yajun3 (AUTHOR), Yao, Lan2,3,4 (AUTHOR), Jiang, Qiuran2,3,4 (AUTHOR) ypqiu@dhu.edu.cn, Qiu, Yiping2,3,4 (AUTHOR) jj@dhu.edu.cn
Publikováno v:
Journal of Adhesion Science & Technology. Apr2015, Vol. 29 Issue 8, p691-704. 14p.