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of 65
pro vyhledávání: '"Wu, Ruiyang"'
This paper introduces a novel framework for dynamic classification in high dimensional spaces, addressing the evolving nature of class distributions over time or other index variables. Traditional discriminant analysis techniques are adapted to learn
Externí odkaz:
http://arxiv.org/abs/2411.01820
Distributed statistical learning has become a popular technique for large-scale data analysis. Most existing work in this area focuses on dividing the observations, but we propose a new algorithm, DDAC-SpAM, which divides the features under a high-di
Externí odkaz:
http://arxiv.org/abs/2205.07932
Autor:
Wu, Ruiyang, Hao, Ning
Discriminant analysis, including linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA), is a popular approach to classification problems. It is well known that LDA is suboptimal to analyze heteroscedastic data, for which QDA wo
Externí odkaz:
http://arxiv.org/abs/2108.09005
Autor:
He, Yifan1 (AUTHOR), Wu, Ruiyang2 (AUTHOR), Zhou, Yong3 (AUTHOR), Feng, Yang2 (AUTHOR) yang.feng@nyu.edu
Publikováno v:
Journal of the American Statistical Association. Sep2024, Vol. 119 Issue 547, p1933-1944. 12p.
Autor:
Wu, Ruiyang1 (AUTHOR), Luo, Jing1 (AUTHOR), Wan, Hangyu1 (AUTHOR), Zhang, Haiyan1 (AUTHOR), Yuan, Yewei1 (AUTHOR), Hu, Huihua1 (AUTHOR), Feng, Jinyan1 (AUTHOR), Wen, Jing1 (AUTHOR), Wang, Yan1 (AUTHOR), Li, Junyan1 (AUTHOR), Liang, Qi1 (AUTHOR), Gan, Fengjiao1 (AUTHOR), Zhang, Gang1 (AUTHOR) 1419174430@qq.com
Publikováno v:
PLoS ONE. 1/26/2023, Vol. 17 Issue 1, p1-15. 15p.
Publikováno v:
In Optics and Laser Technology April 2019 111:372-379
The advances in IC process make future chip multiprocessors (CMPs) more and more vulnerable to transient faults. To detect transient faults, previous core-level schemes provide redundancy for each core separately. As a result, they may leave transien
Externí odkaz:
http://arxiv.org/abs/1206.2132
Akademický článek
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Publikováno v:
In Colloids and Surfaces A: Physicochemical and Engineering Aspects 5 June 2017 522:346-354