Error Density-dependent Empirical Risk Minimization

Chen，Hong1,2,3,4; Zhang，Xuelin1; Gong，Tieliang5; Gu，Bin6; Zheng，Feng7

2024-11-15

10.1016/j.eswa.2024.124332

Expert Systems with Applications   影响因子和分区

0957-4174

Empirical Risk Minimization (ERM) with the squared loss has become one of the most popular principles for designing learning algorithms. However, the existing mean regression models under ERM usually suffer from poor generalization performance due to their sensitivity to atypical observations (e.g., outliers). For alleviating this sensitivity, some strategies have been proposed by utilizing the quantitative relationship of error values with different observations to form robust learning objectives. Instead of focusing on error values, this paper considers the error density to uncover the structure information of observations and proposes a new learning objective, called Error Density-dependent Empirical Risk Minimization (EDERM), for robust regression under complex data environments. Property characterizations and experimental analysis validate the robustness and competitiveness of the proposed EDERM-based learning models. The implemented codes can be found at https://github.com/zhangxuelincode/EDERM.

Empirical risk minimization Error density Kernel regression Robust estimation

SCI ; EI

英语

其他

ENGINEERING

2-s2.0-85195393163

Scopus

1.College of Informatics,Huazhong Agricultural University,Wuhan,430070,China
2.Engineering Research Center of Intelligent Technology for Agriculture,Ministry of Education,Wuhan,430070,China
3.Shenzhen Institute of Nutrition and Health,Huazhong Agricultural University,Shenzhen,518000,China
4.Shenzhen Branch,Guangdong Laboratory for Lingnan Modern Agriculture,Genome Analysis Laboratory of the Ministry of Agriculture,Agricultural Genomics Institute at Shenzhen,Chinese Academy of Agricultural Sciences,Shenzhen,518000,China
5.School of Computer Science and Technology,Xi'an Jiaotong University,Xi'an,710049,China
6.School of Artificial Intelligence,Jilin University,Jilin,130012,China
7.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Chen，Hong,Zhang，Xuelin,Gong，Tieliang,et al. Error Density-dependent Empirical Risk Minimization[J]. Expert Systems with Applications,2024,254.

Chen，Hong,Zhang，Xuelin,Gong，Tieliang,Gu，Bin,&Zheng，Feng.(2024).Error Density-dependent Empirical Risk Minimization.Expert Systems with Applications,254.

Chen，Hong,et al."Error Density-dependent Empirical Risk Minimization".Expert Systems with Applications 254(2024).