Covariate-Elaborated Robust Partial Information Transfer with Conditional Spike-and-Slab Prior
协变量细化的稳健部分信息迁移：条件尖峰-平板先验
The popularity of transfer learning stems from the fact that it can borrow information from useful auxiliary datasets. Existing statistical transfer learning methods usually adopt a global similarity measure between the source data and the target data, which may lead to inefficiency when only partial information is shared. In this paper, we propose a novel Bayesian transfer learning method named ``CONCERT'' to allow robust partial information transfer for high-dimensional…