Zobrazeno 1 - 10
of 361
pro vyhledávání: '"Yao, Weixin"'
Publikováno v:
Neural Information Processing Systems 2023
Supervised matrix factorization (SMF) is a classical machine learning method that simultaneously seeks feature extraction and classification tasks, which are not necessarily a priori aligned objectives. Our goal is to use SMF to learn low-rank latent
Externí odkaz:
http://arxiv.org/abs/2311.11182
Supervised dictionary learning (SDL) is a classical machine learning method that simultaneously seeks feature extraction and classification tasks, which are not necessarily a priori aligned objectives. The goal of SDL is to learn a class-discriminati
Externí odkaz:
http://arxiv.org/abs/2206.06774
A mixture of a distribution of responses from untreated patients and a shift of that distribution is a useful model for the responses from a group of treated patients. The mixture model accounts for the fact that not all the patients in the treated g
Externí odkaz:
http://arxiv.org/abs/2107.06503
Publikováno v:
Journal of Applied Physics; 4/7/2024, Vol. 135 Issue 13, p1-13, 13p
Researchers often have to deal with heterogeneous population with mixed regression relationships, increasingly so in the era of data explosion. In such problems, when there are many candidate predictors, it is not only of interest to identify the pre
Externí odkaz:
http://arxiv.org/abs/2003.04787
Akademický článek
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Publikováno v:
In Journal of Econometrics August 2023 235(2):1001-1026
Publikováno v:
In Automation in Construction July 2023 151
Autor:
Xiang, Sijia, Yao, Weixin
In this article, we introduce a new variable selection technique through trimming for finite mixture of regression models. Compared to the traditional variable selection techniques, the new method is robust and not sensitive to outliers. The estimati
Externí odkaz:
http://arxiv.org/abs/1905.01036