U Statistic

U-statistics are a class of estimators used to estimate population parameters from sample data, particularly useful when dealing with functions of multiple random variables. Current research focuses on improving the efficiency and accuracy of U-statistics in various applications, including data valuation (via Data Shapley), differentially private estimation, and variance reduction in variational inference. These advancements are crucial for addressing challenges in high-dimensional data analysis, privacy-preserving machine learning, and improving the reliability of statistical inference in diverse fields like machine learning and hypothesis testing. The development of novel algorithms and theoretical analyses of U-statistics continues to enhance their applicability and impact across numerous scientific domains.