Refined Graph Encoder Embedding via Self-Training and Latent Community Recovery

arXiv:2405.12797v1 Announce Type: cross
Abstract: This paper introduces a refined graph encoder embedding method, enhancing the original graph encoder embedding using linear transformation, self-training, and hidden community recovery within observed communities. We provide the theoretical rationale for the refinement procedure, demonstrating how and why our proposed method can effectively identify useful hidden communities via stochastic block models, and how the refinement method leads to improved vertex embedding and better decision boundaries for subsequent vertex classification. The efficacy of our approach …

abstract arxiv communities community cs.si embedding encoder graph hidden identify linear paper recovery self-training stat.ml training transformation type via