PERFORMANCE OF EMPIRICAL RISK MINIMIZATION FOR LINEAR REGRESSION WITH DEPENDENT DATA
依赖数据下线性回归经验风险最小化的表现
This paper establishes bounds on the performance of empirical risk minimization for large-dimensional linear regression. We generalize existing results by allowing the data to be dependent and heavy-tailed. The analysis covers both the cases of identically and heterogeneously distributed observations. Our analysis is nonparametric in the sense that the relationship between the regressand and the regressors is not specified. The main results of this paper show that the…