Minh Tang

Minh Tang

Associate Professor

Department of Statistics, North Carolina State University

Interests

  • Statistical inference on graphs
  • Pattern recognition
  • Dimension reduction

Education

  • PhD in Computer Science, 2010

    Indiana University Bloomington

  • MS in Computer Science, 2004

    University of Wisconsin Milwaukee

  • BSc in Computer Science, 2001

    Assumption University, Thailand

Publications

Exact Recovery of Community Structures Using DeepWalk and Node2vec
Yichi Zhang, Minh Tang
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.
Preprint PDF
Hypothesis testing for equality of latent positions in random graphs
Xinjie Du, Minh Tang
Bernoulli, 2023.
Preprint PDF
Numerical tolerance for spectral decompositions of random matrices
Avanti Athreya, Michael Kane, Brian Lewis, Vince Lyzinski, Zachary Lubberts, Youngser Park, Carey E. Priebe, Minh Tang
Journal of Computation and Graphical Statistics, 2023.
Preprint PDF
Popularity adjusted block models are generalized random dot product graphs
John Koo, Minh Tang, Michael Trosset
Journal of Computational and Graphical Statistics, 2023.
Preprint PDF
A statistical interpretation of spectral embedding: the generalised random dot product graph
Patrick Rubin-Delanchy, Joshua Cape, Minh Tang, Carey E. Priebe
Journal of the Royal Statistical Society, Series B, 2022.
Preprint PDF
Vertex nomination between graphs via spectral embedding and quadratic programming
Runbing Zheng, Vince Lyznsiki, Carey E. Priebe, Minh Tang
Journal of Computation and Graphical Statistics, 2022.
Preprint PDF
Valid two-sample graph testing via optimal transport Procrustes and multiscale graph correlation with applications in connectomics
Jaewon Chung, Bijan Varjavand, Jesus Arroyo, Anton Alyakin, Joshua Agterberg, Minh Tang, Joshua T. Vogelstein, Carey E. Priebe
Stat, 2022.
Preprint PDF
Asymptotically efficient estimators for stochastic blockmodels: the naive MLE, the rank-constrained MLE, and the spectral
Minh Tang, Joshua Cape, Carey E. Priebe
Bernoulli, 2022.
Preprint PDF
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings
Keith Levin, Fred Roosta, Minh Tang, Michael W. Mahoney, Carey E. Priebe
Journal of Machine Learning Research, 2021.
Preprint PDF
Eigenvalues of stochastic blockmodel graphs and random graphs with low-rank edge probabilities matrices
Avanti Athreya, Joshua Cape, Minh Tang
Sankhya A, 2021.
Preprint PDF
Supervised dimensionality reduction for big data
Joshua T. Vogelstein, Eric W. Bridgeford, Minh Tang, Da Zheng, Christopher Douville, Randall Burns, Mauro Maggioni
Nature Communications, 2021.
Preprint PDF
On estimation and inference in latent structure random graphs
Avanti Athreya, Minh Tang, Youngser Park, Carey E. Priebe
Statistical Science, 2021.
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A central limit theorem for classical multidimensional scaling
Gongkai Li, Minh Tang, Nicholas Charon, Carey E. Priebe
Electronic Journal of Statistics, 2020.
Preprint PDF
On spectral embedding performance and elucidating network structure
Joshua Cape, Minh Tang, Carey E. Priebe
Journal of Network Science, 2019.
Preprint PDF
Signal-plus-noise matrix models: eigenvector deviations and fluctuations
Joshua Cape, Minh Tang, Carey E. Priebe
Biometrika, 2019.
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The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics
Joshua Cape, Minh Tang, Carey E. Priebe
Annals of Statistics, 2019.
Preprint PDF
On a 'two truths' phenomenon in spectral graph clustering
Carey E. Priebe, Youngser Park, Joshua T. Vogelstein, John M. Conroy, Vince Lyzinski, Minh Tang, Avanti Athreya, Joshua Cape, Eric Bridgeford
Proceedings of the National Academy of Sciences of the USA., 2019.
Preprint PDF
Limit theorems for eigenvectors of the normalized Laplacian for random graphs
Minh Tang, Carey E. Priebe
Annals of Statistics, 2018.
Preprint PDF
Statistical inference on random dot product graphs: a survey
Avanti Athreya, Donniell E. Fishkind, Keith Levin, Vince Lyzinski, Youngser Park, Yichen Qin, Daniel L. Sussman, Minh Tang, Joshua T. Vogelstein, Carey E. Priebe
Journal of Machine Learning Research, 2018.
Preprint PDF
The Kato-Temple inequality and eigenvalue concentration with applications to graph inference
Joshua Cape, Minh Tang, Carey E. Priebe
Electronic Journal of Statistics, 2017.
Preprint PDF
A nonparametric two-sample hypothesis testing problem for random dot product graphs
Minh Tang, Avanti Athreya, Daniel L. Sussman, Vince Lyzinski, Carey E. Priebe
Bernoulli, 2017.
Preprint PDF
A semiparametric two-sample hypothesis testing problem for random dot product graphs
Minh Tang, Avanti Athreya, Daniel L. Sussman, Vince Lyzinski, Youngser Park, Carey E. Priebe
Journal of Computational and Graphical Statistics, 2017.
Preprint PDF
Community detection and classification in hierarchical stochastic blockmodels
Vince Lyzinski, Minh Tang, Avanti Athreya, Youngser Park, Carey E. Priebe
IEEE Transactions on Network Science and Engineering, 2017.
Preprint PDF
Empirical Bayes estimation for the stochastic blockmodels
Shakira Suwan, Dominic S. Lee, Runze Tang, Daniel L. Sussman, Minh Tang, Carey E. Priebe
Electronic Journal of Statistics, 2016.
Preprint PDF
A limit theorem for scaled eigenvectors of random dot product graphs
Avanti Athreya, Carey E. Priebe, Minh Tang, Vince Lyzinski, David J. Marchette, Daniel L. Sussman
Sankhya A, 2016.
Preprint PDF
Statistical inference on errorfully observed graphs
Carey E. Priebe, Daniel L. Sussman, Minh Tang, Joshua T. Vogelstein
Journal of Computational Graphical Statistics, 2015.
Preprint PDF
Generalized canonical correlation analysis for classification
Cencheng Shen, Ming Sun, Minh Tang, Carey E. Priebe
Journal of Multivariate Analysis, 2014.
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Perfect clustering for stochastic blockmodel graphs via adjacency spectral embedding
Vince Lyzinski, Daniel L. Sussman, Minh Tang, Avanti Athreya, Carey E. Priebe
Electronic Journal of Statistics, 2014.
Preprint PDF
Locality statistics for anomaly detection in time series of graphs
Heng Wang, Minh Tang, Youngser Park, Carey E. Priebe
IEEE Transactions on Signal Processing, 2014.
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Consistent latent position estimation and vertex classification for random dot product graphs
Daniel L. Sussman, Minh Tang, Carey E. Priebe
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014.
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On latent position inference from doubly stochastic messaging activities
Nam H. Lee, Jordan Yoder, Minh Tang, Carey E. Priebe
Multiscale Modeling and Simulation, 2013.
Preprint PDF
Universally consistent vertex classification for latent position graphs
Minh Tang, Daniel L. Sussman, Carey E. Priebe
Annals of Statistics, 2013.
Preprint PDF
Attribute fusion in a latent process model for time series of graphs
Minh Tang, Nam H. Lee, Youngser Park, Carey E. Priebe
IEEE Transactions on Signal Processing, 2013.
PDF
Generalized canonical correlation analysis for disparate data fusion
Ming Sun, Minh Tang, Carey E. Priebe
Pattern Recognition Letters, 2013.
Preprint PDF
Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown
Donniell E. Fishkind, Daniel L. Sussman, Minh Tang, Joshua T. Vogelstein, Carey E. Priebe
SIAM Journal on Matrix Analysis and Applications, 2013.
Preprint PDF
A consistent adjacency spectral embedding for stochastic blockmodel graphs
Daniel L. Sussman, Minh Tang, Donniell E. Fishkind, Carey E. Priebe
Journal of the American Statistical Association, 2012.
Preprint PDF

Preprints

Limit results for distributed estimation of invariant subspaces in multiple networks inference and PCA
Runbing Zheng, Minh Tang
arXiv preprint, 2022.
Preprint
Perturbation analysis of randomized SVD and its applications to high-dimensional statistics
Yichi Zhang, Minh Tang
arXiv preprint, 2022.
Preprint
Adversarial contamination of networks in the setting of vertex nomination: a new trimming method
Sheyda Peyman, Minh Tang, Vince Lyzinski
arXiv preprint, 2022.
Preprint
Classification of high-dimensional data with spiked covariance matrix structure
Yin-Jen Chen, Minh Tang
arXiv preprint, 2021.
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Nonparametric Two-Sample Hypothesis Testing for Random Graphs with Negative and Repeated Eigenvalues
Joshua Agteberg, Minh Tang, Carey E. Priebe
Arxiv preprint, 2020.
Preprint
Two-sample testing on latent distance graphs with unknown link functions
Yiran Wang, Minh Tang, Soumendra N. Lahiri
arXiv preprint, 2020.
Preprint
Learning 1-dimensional submanifolds for subsequent inference on random dot product graphs
Michael W. Trosset, Mingyue Gao, Minh Tang, Carey E. Priebe
Arxiv preprint, 2020.
Preprint
On two distinct sources of non-identifiability in latent position random graph models
Joshua Agteberg, Minh Tang, Carey E. Priebe
Arxiv preprint, 2020.
Preprint
A central limit theorem for an omnibus embedding of random dot product graphs
Keith Levin, Avanti Athreya, Minh Tang, Vince Lyzinski, Carey E. Priebe
Arxiv preprint, 2017.
Preprint
Robust estimation from multiple graphs under gross error contamination
Runze Tang, Minh Tang, Joshua T. Vogelstein, Carey E. Priebe
Arxiv preprint, 2017.
Preprint

Teaching

Statistical inference on graphs

Contact