论文标题
用重尾噪声和协变量对线性回归系数的强大和稀疏估计
Robust and Sparse Estimation of Linear Regression Coefficients with Heavy-tailed Noises and Covariates
论文作者
论文摘要
研究了线性回归系数的稳健和稀疏估计。本文解决的情况是，协变量和噪音是从重型分布中取样的，而协变量和噪音被恶意异常值污染。我们的估计器可以有效地计算。此外，估计器的误差界限几乎是最佳的。
Robust and sparse estimation of linear regression coefficients is investigated. The situation addressed by the present paper is that covariates and noises are sampled from heavy-tailed distributions, and the covariates and noises are contaminated by malicious outliers. Our estimator can be computed efficiently. Further, the error bound of the estimator is nearly optimal.
