Bin Liu

A General U-Statistic Framework for High-Dimensional Multiple Change-Point Analysis

High-dimensional change-point analysis is essential in modern statistical inference. However, existing methods are often designed either for specific parameters (e.g., mean or variance) or for particular tasks (e.g., testing or estimation), making them difficult to generalize. Moreover, they typically rely on restricti...