Follow
Minh Tang
Title
Cited by
Cited by
Year
A consistent adjacency spectral embedding for stochastic blockmodel graphs
DL Sussman, M Tang, DE Fishkind, CE Priebe
Journal of the American Statistical Association 107 (499), 1119-1128, 2012
3072012
Statistical inference on random dot product graphs: a survey
A Athreya, DE Fishkind, M Tang, CE Priebe, Y Park, JT Vogelstein, ...
Journal of Machine Learning Research 18 (226), 1-92, 2018
2542018
Community detection and classification in hierarchical stochastic blockmodels
V Lyzinski, M Tang, A Athreya, Y Park, CE Priebe
IEEE Transactions on Network Science and Engineering 4 (1), 13-26, 2016
1592016
The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics
J Cape, M Tang, CE Priebe
1412019
A limit theorem for scaled eigenvectors of random dot product graphs
A Athreya, CE Priebe, M Tang, V Lyzinski, DJ Marchette, DL Sussman
Sankhya A 78, 1-18, 2016
1412016
Universally consistent vertex classification for latent positions graphs
M Tang, DL Sussman, CE Priebe
1392013
A semiparametric two-sample hypothesis testing problem for random graphs
M Tang, A Athreya, DL Sussman, V Lyzinski, Y Park, CE Priebe
Journal of Computational and Graphical Statistics 26 (2), 344-354, 2017
1362017
Perfect clustering for stochastic blockmodel graphs via adjacency spectral embedding
V Lyzinski, DL Sussman, M Tang, A Athreya, CE Priebe
1302014
A statistical interpretation of spectral embedding: the generalised random dot product graph
P Rubin-Delanchy, J Cape, M Tang, CE Priebe
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022
1212022
Consistent latent position estimation and vertex classification for random dot product graphs
DL Sussman, M Tang, CE Priebe
IEEE transactions on pattern analysis and machine intelligence 36 (1), 48-57, 2013
1182013
Locality statistics for anomaly detection in time series of graphs
H Wang, M Tang, Y Park, CE Priebe
IEEE Transactions on Signal Processing 62 (3), 703-717, 2013
1152013
Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown
DE Fishkind, DL Sussman, M Tang, JT Vogelstein, CE Priebe
SIAM Journal on Matrix Analysis and Applications 34 (1), 23-39, 2013
1142013
Limit theorems for eigenvectors of the normalized Laplacian for random graphs
M Tang, CE Priebe
1132018
A nonparametric two-sample hypothesis testing problem for random graphs
M Tang, A Athreya, DL Sussman, V Lyzinski, CE Priebe
109*2017
A central limit theorem for an omnibus embedding of multiple random dot product graphs
K Levin, A Athreya, M Tang, V Lyzinski, CE Priebe
2017 IEEE international conference on data mining workshops (ICDMW), 964-967, 2017
92*2017
On a two-truths phenomenon in spectral graph clustering
CE Priebe, Y Park, JT Vogelstein, JM Conroy, V Lyzinski, M Tang, ...
Proceedings of the National Academy of Sciences 116 (13), 5995-6000, 2019
822019
Signal-plus-noise matrix models: eigenvector deviations and fluctuations
J Cape, M Tang, CE Priebe
Biometrika 106 (1), 243-250, 2019
642019
Statistical inference on errorfully observed graphs
CE Priebe, DL Sussman, M Tang, JT Vogelstein
Journal of Computational and Graphical Statistics 24 (4), 930-953, 2015
522015
Supervised dimensionality reduction for big data
JT Vogelstein, EW Bridgeford, M Tang, D Zheng, C Douville, R Burns, ...
Nature communications 12 (1), 2872, 2021
46*2021
On estimation and inference in latent structure random graphs
A Athreya, M Tang, Y Park, CE Priebe
462021
The system can't perform the operation now. Try again later.
Articles 1–20