Bayesian Transfer Learning for High-Dimensional Linear Regression via Adaptive Shrinkage
基于自适应收缩的高维线性回归贝叶斯迁移学习
We introduce BLAST, Bayesian Linear regression with Adaptive Shrinkage for Transfer, a Bayesian multi-source transfer learning framework for high-dimensional linear regression. The proposed analytical framework leverages global-local shrinkage priors together with Bayesian source selection to balance information sharing and regularization. We show how Bayesian source selection allows for the extraction of the most useful data sources, while discounting biasing information…