A0544
Title: Efficient analysis of latent spaces in heterogeneous networks
Authors: Yinqiu He - University of Wisconsin - Madison (United States) [presenting]
Abstract: A unified framework is proposed for efficient estimation under latent space modeling of heterogeneous networks. A class of latent space models is considered that decomposes latent vectors into shared and network-specific components across networks. A novel procedure is developed that first identifies the shared latent vectors and further refines estimates through efficient score equations to achieve statistical efficiency. Oracle error rates for estimating the shared and heterogeneous latent vectors are established simultaneously. The analysis framework offers remarkable flexibility, accommodating various types of edge weights under general distributions.
