Outlier Robust Extreme Machine Learning for multi-target regression
作者：
Highlights：
• Handles Multi-Target Regression Problems.
• Generalized Outlier Robust Extreme Learning Machine.
• Shows robustness when training data is contaminated with outliers.
• Training time is similar to Generalized and Outlier-Robust Extreme Learning Machines.
• An incremental version of the method is presented.
摘要
•Handles Multi-Target Regression Problems.•Generalized Outlier Robust Extreme Learning Machine.•Shows robustness when training data is contaminated with outliers.•Training time is similar to Generalized and Outlier-Robust Extreme Learning Machines.•An incremental version of the method is presented.
论文关键词：ℓ2,1 norm,Extreme Learning Machine,Regularization,Multi-target regression,Robust to outliers,Alternating direction method of multipliers
论文评审过程：Received 17 April 2019, Revised 15 July 2019, Accepted 16 August 2019, Available online 17 August 2019, Version of Record 29 August 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.112877
