KMS National Astronomical Observatories, CAS
| Robust Gaussian process regression based on iterative trimming | |
| Li, Zhao-Zhou1; Li, Lu2,3; Shao, Zhengyi2,4 | |
| 2021-07-01 | |
| Source Publication | ASTRONOMY AND COMPUTING
 |
| ISSN | 2213-1337 |
| Volume | 36Pages:10 |
| Abstract | The Gaussian process (GP) regression can be severely biased when the data are contaminated by outliers. This paper presents a new robust GP regression algorithm that iteratively trims the most extreme data points. While the new algorithm retains the attractive properties of the standard GP as a nonparametric and flexible regression method, it can greatly improve the model accuracy for contaminated data even in the presence of extreme or abundant outliers. It is also easier to implement compared with previous robust GP variants that rely on approximate inference. Applied to a wide range of experiments with different contamination levels, the proposed method significantly outperforms the standard GP and the popular robust GP variant with the Student-t likelihood in most test cases. In addition, as a practical example in the astrophysical study, we show that this method can precisely determine the main-sequence ridge line in the color-magnitude diagram of star clusters. (C) 2021 Elsevier B.V. All rights reserved. |
| Keyword | Gaussian process Robust regression Outlier detection Ridge line Star clusters |
| Funding Organization | National Key Basic R&D Pro-gram of China ; National Key Basic R&D Pro-gram of China ; NSFC, China ; NSFC, China ; 111 project, China ; 111 project, China ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; National Key Basic R&D Pro-gram of China ; National Key Basic R&D Pro-gram of China ; NSFC, China ; NSFC, China ; 111 project, China ; 111 project, China ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; National Key Basic R&D Pro-gram of China ; National Key Basic R&D Pro-gram of China ; NSFC, China ; NSFC, China ; 111 project, China ; 111 project, China ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; National Key Basic R&D Pro-gram of China ; National Key Basic R&D Pro-gram of China ; NSFC, China ; NSFC, China ; 111 project, China ; 111 project, China ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education |
| DOI | 10.1016/j.ascom.2021.100483 |
| WOS Keyword | EFFICIENCY ; LTS |
| Language | 英语 |
| Funding Project | National Key Basic R&D Pro-gram of China[2018YFA0404504] ; National Key Basic R&D Pro-gram of China[2019YFA0405501] ; NSFC, China[11621303] ; NSFC, China[11873038] ; NSFC, China[11890691] ; NSFC, China[11973032] ; NSFC, China[12022307] ; NSFC, China[U2031139] ; 111 project, China[B20019] ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education |
| Funding Organization | National Key Basic R&D Pro-gram of China ; National Key Basic R&D Pro-gram of China ; NSFC, China ; NSFC, China ; 111 project, China ; 111 project, China ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; National Key Basic R&D Pro-gram of China ; National Key Basic R&D Pro-gram of China ; NSFC, China ; NSFC, China ; 111 project, China ; 111 project, China ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; National Key Basic R&D Pro-gram of China ; National Key Basic R&D Pro-gram of China ; NSFC, China ; NSFC, China ; 111 project, China ; 111 project, China ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; National Key Basic R&D Pro-gram of China ; National Key Basic R&D Pro-gram of China ; NSFC, China ; NSFC, China ; 111 project, China ; 111 project, China ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education ; MOE Key Lab for Particle Physics, Astrophysics and Cosmology, Ministry of Education |
| WOS Research Area | Astronomy & Astrophysics ; Computer Science |
| WOS Subject | Astronomy & Astrophysics ; Computer Science, Interdisciplinary Applications |
| WOS ID | WOS:000691531100010 |
| Publisher | ELSEVIER |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.bao.ac.cn/handle/114a11/75380 |
| Collection | 中国科学院国家天文台 |
| Corresponding Author | Li, Zhao-Zhou |
| Affiliation | 1.Shanghai Jiao Tong Univ, Sch Phys & Astron, Dept Astron, 955 Jianchuan Rd, Shanghai 200240, Peoples R China 2.Chinese Acad Sci, Shanghai Astron Observ, Key Lab Res Galaxies & Cosmol, 80 Nandan Rd, Shanghai 200030, Peoples R China 3.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China 4.Key Lab Astrophys, Shanghai 200234, Peoples R China |
| Recommended Citation GB/T 7714 | Li, Zhao-Zhou,Li, Lu,Shao, Zhengyi. Robust Gaussian process regression based on iterative trimming[J]. ASTRONOMY AND COMPUTING,2021,36:10. |
| APA | Li, Zhao-Zhou,Li, Lu,&Shao, Zhengyi.(2021).Robust Gaussian process regression based on iterative trimming.ASTRONOMY AND COMPUTING,36,10. |
| MLA | Li, Zhao-Zhou,et al."Robust Gaussian process regression based on iterative trimming".ASTRONOMY AND COMPUTING 36(2021):10. |
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