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.AP2025
Kernel Density Balancing
John Park, Ning Hao, Yue Selena Niu +1
High-throughput chromatin conformation capture (Hi-C) data provide insights into the 3D structure of chromosomes, with normalization being a crucial pre-processing step. A common t…
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…