CONCERT: Covariate-Elaborated Robust Local Information Transfer with Conditional Spike-and-Slab Prior

arXiv:2404.03764v1 Announce Type: new
Abstract: 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 local information is shared. In this paper, we propose a novel Bayesian transfer learning method named "CONCERT" to allow robust local information transfer for high-dimensional data analysis. A novel conditional spike-and-slab …

abstract arxiv cs.lg data datasets global information prior robust source data statistical stat.me stat.ml transfer transfer learning type