Tuning-Free Covariance-Aware Sequential Shrinkage for Multi-Source Estimation

Modern statistical learning problems often involve multiple related data sets, in which learning efficiency on a target set can be improved by borrowing information from related sources, while source heterogeneity may introduce bias. Existing approaches are limited by suboptimal performance in multi