118 citations · 602 across the 43 of their papers we have counts for
5 papers · 1 filter
Perfect Clustering for Stochastic Blockmodel Graphs via Adjacency Spectral Embedding
Vince Lyzinski, Daniel Sussman, Minh Tang +2
Vertex clustering in a stochastic blockmodel graph has wide applicability and has been the subject of extensive research. In thispaper, we provide a short proof that the adjacency…
Locality statistics for anomaly detection in time series of graphs
Heng Wang, Minh Tang, Youngser Park +1
The ability to detect change-points in a dynamic network or a time series of graphs is an increasingly important task in many applications of the emerging discipline of graph signa…
Out-of-sample Extension for Latent Position Graphs
Minh Tang, Youngser Park, Carey E. Priebe
We consider the problem of vertex classification for graphs constructed from the latent position model. It was shown previously that the approach of embedding the graphs into some…
A central limit theorem for scaled eigenvectors of random dot product graphs
Avanti Athreya, Vince Lyzinski, David J. Marchette +3
We prove a central limit theorem for the components of the largest eigenvectors of the adjacency matrix of a finite-dimensional random dot product graph whose true latent positions…
Generalized Canonical Correlation Analysis for Classification
Cencheng Shen, Ming Sun, Minh Tang +1
For multiple multivariate data sets, we derive conditions under which Generalized Canonical Correlation Analysis (GCCA) improves classification performance of the projected dataset…