3 papers
stat.ML2026
Spectral Embeddings of Degree- Laplacians in Random Dot Product Graphs
John Park, Ning Hao
Spectral clustering methods for network data are commonly based on a few matrix representations, such as the adjacency matrix and the symmetric Laplacian. We study a continuum of d…
stat.ME2025
A Note on the Identifiability of the Degree-Corrected Stochastic Block Model
John Park, Yunpeng Zhao, Ning Hao
In this short note, we address the identifiability issues inherent in the Degree-Corrected Stochastic Block Model (DCSBM). We provide a rigorous proof demonstrating that the parame…
stat.ML2024
Community Detection with Heterogeneous Block Covariance Model
Xiang Li, Yunpeng Zhao, Qing Pan +1
Community detection is the task of clustering objects based on their pairwise relationships. Most of the model-based community detection methods, such as the stochastic block model…