AbstractSchatten p-quasi-norm minimization has advantages over nuclear norm minimization in recovering low-rank matrices. However, Schatten p-quasi-norm minimization is much more difficult, especially for generic linear matrix equations. We first extend the lower bound theory of l_p minimization to Schatten p-quasi-norm minimization. Motivated by this property, we propose a proximal linearizati...
Statistical SeminarOrganizer:吴宇楠Speaker:戴奔 助理教授香港中文大学统计与数据科学系Time:Fri., 16:00-17:00, April 24, 2026Venue:C654, Shuangqing Complex Building ATitle:ReHLine: Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear ConvergenceAbstract:Empirical risk minimization (ERM) is a crucial framework that offers a general approach to handling a broad r...