重尾噪声与协变量下线性回归系数的稳健稀疏估计
机器学习
2022-10-11 v3 机器学习
摘要
本文研究线性回归系数的稳健与稀疏估计。本文所考虑的情形是：协变量与噪声采样自重尾分布，且协变量与噪声受到恶意离群点的污染。我们的估计量可高效计算。此外，该估计量的误差界近乎最优。
引用
@article{arxiv.2206.07594,
title = {Robust and Sparse Estimation of Linear Regression Coefficients with Heavy-tailed Noises and Covariates},
author = {Takeyuki Sasai},
journal= {arXiv preprint arXiv:2206.07594},
year = {2022}
}
备注
Some mistakes are corrected, and one assumption is added to the main theorem