Robust regression framework with asymmetrically analogous to correntropy-induced loss
作者：
Highlights：
• Propose an analogous to correntropy-induced loss ( RE-loss).
• RE-loss is an exponential expectile penalty.
• A sparse version of RE-loss is built with a ϵ-insensitive version.
• Demonstrate important properties of RE-loss function.
• RE-loss includes and extends the existing loss functions.
摘要
•Propose an analogous to correntropy-induced loss ( RE-loss).•RE-loss is an exponential expectile penalty.•A sparse version of RE-loss is built with a ϵ-insensitive version.•Demonstrate important properties of RE-loss function.•RE-loss includes and extends the existing loss functions.
论文关键词：Robustness,Asymmetry least square loss,Expectile,Nonconvexity,Correntropy,Regression,CCCP
论文评审过程：Received 13 January 2019, Revised 7 November 2019, Accepted 7 November 2019, Available online 11 November 2019, Version of Record 8 February 2020.
论文官网地址：https://doi.org/10.1016/j.knosys.2019.105211
