Learning Joint Graphical Model with Computational Efficiency, Dynamic Regularization, and Adaptation

Multi-sourced datasets are common in studies of variable interactions, for example, heterogeneous gene networks, cross-domain recommendation, etc., where each source induces a related but distinct dependency structure. Joint learning of multiple graphical models (i.e., multiple precision matrices) h