Self-Supervised Random Forest on Transformed Distribution for Anomaly Detection-Reference-Cited by-同舟云学术

Self-Supervised Random Forest on Transformed Distribution for Anomaly Detection

Author:

Liu Jiabin¹^ORCID,Wang Huadong²^ORCID,Hang Hanyuan³,Ma Shumin⁴^ORCID,Shen Xin⁵^ORCID,Shi Yong⁶^ORCID

Affiliation:

1. School of Information and Electronics, Beijing Institute of Technology, Beijing, China

2. ModelBest Inc, Beijing, China

3. Department of Applied Mathematics, University of Twente, Enschede, The Netherlands

4. Guangdong Provincial Key Laboratory IRADS and the Department of Mathematical Science, BNU-HKBU United International College, Zhuhai, China

5. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China

6. School of Economics and Management, University of Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science

Guangdong Higher Education Upgrading Plan

Beijing Normal University-Hong Kong Baptist University United International College

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

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