Sub-Gaussian estimators of the mean of a random vector
针对随机向量均值估计问题，提出一种仅需二阶矩存在即可达到次高斯性能的新估计量，基于多元中位数概念。
We study the problem of estimating the mean of a random vector $X$ given a sample of $N$ independent, identically distributed points. We introduce a new estimator that achieves a purely sub-Gaussian performance under the only condition that the second moment of $X$ exists. The estimator is based on a novel concept of a multivariate median.