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Wishart随机矩阵的数据拆分AI 解读

Summary Recent work has explored data thinning, a generalization of sample splitting that involves decomposing a (possibly matrix-valued) random variable into independent components. In the special case of an $ n\times p $ random matrix with independent and identically distributed $ N_{p}(\mu,\Sigma) $ rows, Dharamshi et al. (2026)provided a comprehensive analysis of the settings in which thinning is or is not possible: briefly, if $ \Sigma $ is unknown then one can thin…

未知协方差下的高斯信息分解AI 解读

Abstract Common workflows in machine learning and statistics rely on the ability to partition the information in a dataset into independent portions. Recent work has shown that this may be possible even when conventional sample splitting is not, such as when the number of samples, $ n $, is one or when observations are not independent and identically distributed. In the case of multivariate Gaussian data, these alternatives to sample splitting require knowledge of the…