Gaussian Process Regression with Grid Spectral Mixture Kernel: Distributed Learning for Multidimensional Data-Reference-Cited by-同舟云学术

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Gaussian Process Regression with Grid Spectral Mixture Kernel: Distributed Learning for Multidimensional Data

Published:2022-07-04 Issue: Volume: Page:
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Container-title:2022 25th International Conference on Information Fusion (FUSION)
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Author:

Suwandi Richard Cornelius¹,Lin Zhidi²,Sun Yiyong²,Wang Zhiguo³,Cheng Lei⁴,Yin Feng²

Affiliation:

1. School of Data Science, The Chinese University of Hong Kong,Shenzhen,China

2. School of Science and Engineering, The Chinese University of Hong Kong,Shenzhen,China

3. College of Mathematics, Sichuan University,Chengdu,China

4. College of Information Science and Electronic Engineering, Zhejiang University,Hangzhou,China

Funder

Natural Science Foundation of China (NSFC)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9841224/9841225/09841347.pdf?arnumber=9841347

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2. Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

3. Output-Dependent Gaussian Process State-Space Model;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

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