most citedDual regularized Laplacian spectral clustering methods on community detection

2 citations · 5 across the 7 of their papers we have counts for

collaborators

8 papers

stat.ME20211 cited

Impact of regularization on spectral clustering under the mixed membership stochastic block model

Huan Qing, Jingli Wang

Mixed membership community detection is a challenge problem in network analysis. To estimate the memberships and study the impact of regularized spectral clustering under the mixed…

cs.SI2020

An improved spectral clustering method for mixed membership community detection

Huan Qing, Jingli Wang

Community detection has been well studied recent years, but the more realistic case of mixed membership community detection remains a challenge. Here, we develop an efficient spect…

cs.SI2020

Mixed-SCORE+ for mixed membership community detection

Huan Qing, Jingli Wang

Mixed-SCORE is a recent approach for mixed membership community detection proposed by Jin et al. (2017) which is an extension of SCORE (Jin, 2015). In the note Jin et al. (2018), t…

stat.ML20201 cited

An improved spectral clustering method for community detection under the degree-corrected stochastic blockmodel

Huan Qing, Jingli Wang

For community detection problem, spectral clustering is a widely used method for detecting clusters in networks. In this paper, we propose an improved spectral clustering (ISC) app…

stat.ML20201 cited

Community Detection by Principal Components Clustering Methods

Huan Qing, Jingli Wang

Based on the classical Degree Corrected Stochastic Blockmodel (DCSBM) model for network community detection problem, we propose two novel approaches: principal component clustering…

stat.ML20202 cited

Dual regularized Laplacian spectral clustering methods on community detection

Huan Qing, Jingli Wang

Spectral clustering methods are widely used for detecting clusters in networks for community detection, while a small change on the graph Laplacian matrix could bring a dramatic im…