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Yongdao Zhou on Muck Rack

Yongdao Zhou

As seen in: arXiv, MDPI, Taylor & Francis Online
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Articles

Sparsification Subsampling for Partial Least Squares Regression

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By Junyi Lin, Mengyu Li, Yongdao Zhou
| Taylor & Francis Online
Abstract Partial Least Squares (PLS) regression is a powerful tool for dimensionality reduction, multi-response variable regression, and multi-classification. However, its application to large-scale datasets is often hampered by significant computational burdens. Although variants of PLS algorithms have been proposed to address this challenge, an efficient algorithm that significantly reduces the time complexity remains underexplored.
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Construction of Uniform Designs over a Domain with Linear Constraints

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By Xiaoping Yang, Yongdao Zhou, Luojing Yang
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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MODE: Minimax Optimal Deterministic Experiments for Causal Inference in the Presence of Covariates

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By Shaohua Xu, Songnan Liu, Yongdao Zhou
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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