Large-scale heteroscedastic regression via Gaussian process

Large-scale heteroscedastic regression via Gaussian process

Heteroscedastic regression considering the varying noises among observations has many applications in the fields, such as machine learning and statistics. Here, we focus on the heteroscedastic Gaussian process (HGP) regression that integrates the latent function and the noise function in a unified n...

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書目詳細資料
Main Authors:	Liu, Haitao, Ong, Yew-Soon, Cai, Jianfei
其他作者:	School of Computer Science and Engineering
格式:	Article
語言:	English
出版:	2022
主題:	Engineering::Computer science and engineering Distributed Learning Sparse Approximation
在線閱讀:	https://hdl.handle.net/10356/159646
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Nanyang Technological University
語言:	English

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