Optimal Composite Likelihood Estimation and Prediction for Distributed Gaussian Process Modeling-Reference-Cited by-同舟云学术

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Optimal Composite Likelihood Estimation and Prediction for Distributed Gaussian Process Modeling

Published:2024-02 Issue:2 Volume:46 Page:1134-1147
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Li Yongxiang¹^ORCID,Zhou Qiang²^ORCID,Jiang Wei³^ORCID,Tsui Kwok-Leung⁴^ORCID

Affiliation:

1. Department of Industrial Engineering and Management, Shanghai Jiao Tong University, Shanghai, China

2. Meta, Menlo Park, CA, USA

3. Department of Management Science, Shanghai Jiao Tong University, Shanghai, China

4. Department of Industrial Engineering and Management, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanghai

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/10384454/10301563.pdf?arnumber=10301563

Reference44 articles.

1. Wiley Series in Probability and Statistics

2. The Design and Analysis of Computer Experiments

3. Hyperspectral Recovery from RGB Images using Gaussian Processes

4. Minimizing Negative Transfer of Knowledge in Multivariate Gaussian Processes: A Scalable and Regularized Approach

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