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- W3094965248 abstract "Neural networks are becoming an increasingly important tool in applications. However, neural networks are not widely used in statistical genetics. In this paper, we propose a new neural networks method called expectile neural networks. When the size of parameter is too large, the standard maximum likelihood procedures may not work. We use sieve method to constrain parameter space. And we prove its consistency and normality under nonparametric regression framework." @default.
- W3094965248 created "2020-11-09" @default.
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- W3094965248 date "2020-10-30" @default.
- W3094965248 modified "2023-09-26" @default.
- W3094965248 title "Asymptotic Theory of Expectile Neural Networks" @default.
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- W3094965248 doi "https://doi.org/10.48550/arxiv.2011.01218" @default.
- W3094965248 hasPublicationYear "2020" @default.
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