In the context of a high-dimensional linear regression model, we propose use an empirical correlation-adaptive prior that makes information in observed predictor variable matrix to adaptively address high collinearity, determining if parameters associated with correlated predictors should be shrunk together or kept apart. Under suitable conditions, prove this Bayes posterior concentrates around...