Large-scale non-negative subspace clustering based on nyström approximation
H Jia, Q Ren, L Huang, Q Mao, L Wang, H Song - Information Sciences, 2023 - Elsevier
Large-scale subspace clustering usually drops the requirements of the full similarity matrix
and Laplacian matrix but constructs the anchor affinity matrix and uses matrix approximation …
and Laplacian matrix but constructs the anchor affinity matrix and uses matrix approximation …
Subsampling spectral clustering for stochastic block models in large-scale networks
The rapid development of science and technology has generated large amounts of network
data, leading to significant computational challenges for network community detection. A …
data, leading to significant computational challenges for network community detection. A …
Privacy-preserving community detection for locally distributed multiple networks
An Overview of Asymptotic Normality in Stochastic Blockmodels: Cluster Analysis and Inference
This paper provides a selective review of the statistical network analysis literature focused
on clustering and inference problems for stochastic blockmodels and their variants. We …
on clustering and inference problems for stochastic blockmodels and their variants. We …
[HTML][HTML] Traffic demand prediction using a social multiplex networks representation on a multimodal and multisource dataset
In this paper, a meaningful representation of the road network using multiplex networks and
a novel feature selection framework that enhances the predictability of future traffic …
a novel feature selection framework that enhances the predictability of future traffic …
Degree-corrected distribution-free model for community detection in weighted networks
H Qing - Scientific Reports, 2022 - nature.com
A degree-corrected distribution-free model is proposed for weighted social networks with
latent structural information. The model extends the previous distribution-free models by …
latent structural information. The model extends the previous distribution-free models by …
Subsampling-based modified bayesian information criterion for large-scale stochastic block models
Identifying the number of communities is a fundamental problem in community detection,
which has received increasing attention recently. However, rapid advances in technology …
which has received increasing attention recently. However, rapid advances in technology …
Estimating mixed memberships in directed networks by spectral clustering
H Qing - Entropy, 2023 - mdpi.com
Community detection is an important and powerful way to understand the latent structure of
complex networks in social network analysis. This paper considers the problem of estimating …
complex networks in social network analysis. This paper considers the problem of estimating …