M. Tang

发表

Metric Space Structures for Computational Anatomy

Xiaoying Tang, Carey E. Priebe, Michael I. Miller, 2013, MLMI.

Numerical Tolerance for Spectral Decompositions of Random Matrices and Applications to Network Inference

C. Priebe, V. Lyzinski, A. Athreya, 2016, Journal of Computational and Graphical Statistics.

On Estimation and Inference in Latent Structure Random Graphs

C. Priebe, Minh Tang, A. Athreya, 2018, Statistical Science.

Numerical tolerance for spectral decompositions of random dot product graphs

Carey E. Priebe, Bryan Lewis, Vince Lyzinski, 2016, 1608.00451.

Statistical Inference on Errorfully Observed Graphs

Carey E. Priebe, Daniel L. Sussman, Joshua T. Vogelstein, 2012, 1211.3601.

Vertex Nomination Between Graphs via Spectral Embedding and Quadratic Programming

C. Priebe, V. Lyzinski, M. Tang, 2020, Journal of Computational and Graphical Statistics.

Asymptotically efficient estimators for stochastic blockmodels: The naive MLE, the rank-constrained MLE, and the spectral estimator

C. Priebe, Joshua Cape, M. Tang, 2017, Bernoulli.

Statistical Inference on Random Dot Product Graphs: a Survey

Carey E. Priebe, Donniell E. Fishkind, Daniel L. Sussman, 2017, J. Mach. Learn. Res..

The Kato–Temple inequality and eigenvalue concentration with applications to graph inference

C. Priebe, Joshua Cape, Minh Tang, 2016, 1603.06100.

The Kato-Temple inequality and eigenvalue concentration

C. Priebe, Joshua Cape, Minh Tang, 2016 .

A Limit Theorem for Scaled Eigenvectors of Random Dot Product Graphs

C. Priebe, V. Lyzinski, D. Sussman, 2013, Sankhya A.

Two-sample Hypothesis Testing for Random Dot Product Graphs via Adjacency Spectral Embedding

Carey E. Priebe, Daniel L. Sussman, Minh Tang, 2014 .

A nonparametric two-sample hypothesis testing problem for random dot product graphs

C. Priebe, V. Lyzinski, D. Sussman, 2014, 1409.2344.

A central limit theorem for scaled eigenvectors of random dot product graphs

David J. Marchette, Carey E. Priebe, Daniel L. Sussman, 2013, 1305.7388.

Consistent Adjacency-Spectral Partitioning for the Stochastic Block Model When the Model Parameters Are Unknown

Carey E. Priebe, Donniell E. Fishkind, Daniel L. Sussman, 2012, SIAM J. Matrix Anal. Appl..

A Consistent Adjacency Spectral Embedding for Stochastic Blockmodel Graphs

Carey E. Priebe, Donniell E. Fishkind, Daniel L. Sussman, 2011, 1108.2228.

A consistent dot product embedding for stochastic blockmodel graphs

Carey E. Priebe, Donniell E. Fishkind, Daniel L. Sussman, 2011 .

Hypothesis testing for equality of latent positions in random graphs

Xinjie Du, M. Tang, 2021, Bernoulli.

Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings pdf

Carey E. Priebe, Michael W. Mahoney, Fred Roosta, 2019, J. Mach. Learn. Res..

Limit theorems for eigenvectors of the normalized Laplacian for random graphs

Carey E. Priebe, Minh Tang, C. Priebe, 2016, The Annals of Statistics.

Out-of-sample Extension for Latent Position Graphs

C. Priebe, Minh Tang, Youngser Park, 2013, 1305.4893.

Graph metrics and dimension reduction

M. Trosset, Minh Tang, M. Tang, 2010 .

Robust Estimation from Multiple Graphs under Gross Error Contamination

Carey E. Priebe, Joshua T. Vogelstein, Minh Tang, 2017, 1707.03487.

A central limit theorem for an omnibus embedding of multiple random graphs and implications for multiscale network inference

Carey E. Priebe, Youngser Park, Minh Tang, 2017 .

A central limit theorem for an omnibus embedding of random dot product graphs

C. Priebe, V. Lyzinski, Keith Levin, 2017, 1705.09355.

Semiparametric spectral modeling of the Drosophila connectome

C. Priebe, A. Cardona, J. Vogelstein, 2017, 1705.03297.

A Semiparametric Two-Sample Hypothesis Testing Problem for Random Graphs

C. Priebe, V. Lyzinski, D. Sussman, 2017 .

Community Detection and Classification in Hierarchical Stochastic Blockmodels

Carey E. Priebe, Vince Lyzinski, Youngser Park, 2015, IEEE Transactions on Network Science and Engineering.

Universally Consistent Latent Position Estimation and Vertex Classification for Random Dot Product Graphs

Carey E. Priebe, Daniel L. Sussman, Minh Tang, 2012, 1207.6745.

Perfect Clustering for Stochastic Blockmodel Graphs via Adjacency Spectral Embedding

C. Priebe, V. Lyzinski, D. Sussman, 2013, 1310.0532.

Universally consistent vertex classification for latent positions graphs

C. Priebe, D. Sussman, Minh Tang, 2012, 1212.1182.

Signal‐plus‐noise matrix models: eigenvector deviations and fluctuations

C. Priebe, Joshua Cape, Minh Tang, 2018, Biometrika.

The two-to-infinity norm and singular subspace geometry with applications to high-dimensional statistics

C. Priebe, Joshua Cape, Minh Tang, 2017, The Annals of Statistics.

A statistical interpretation of spectral embedding: The generalised random dot product graph pdf

Carey E. Priebe, Patrick Rubin-Delanchy, Minh Tang, 2017, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Attribute Fusion in a Latent Process Model for Time Series of Graphs

Carey E. Priebe, Youngser Park, Minh Tang, 2011, IEEE Transactions on Signal Processing.

On a two-truths phenomenon in spectral graph clustering

Carey E. Priebe, John M. Conroy, Joshua T. Vogelstein, 2018, Proceedings of the National Academy of Sciences.

Generalized canonical correlation analysis for classification

Carey E. Priebe, Cencheng Shen, Ming Sun, 2013, J. Multivar. Anal..

Supervised dimensionality reduction for big data

Eric W. Bridgeford, J. Vogelstein, Da Zheng, 2021, Nature Communications.

Geometric Dimensionality Reduction for Subsequent Classification

Eric W. Bridgeford, J. Vogelstein, Da Zheng, 2017, 1709.01233.

On Combinatorial Laplacian Eigenmaps

Michael W. Trosset, Minh Tang, M. Trosset, 2010 .

A Central Limit Theorem for an Omnibus Embedding of Multiple Random Dot Product Graphs

Carey E. Priebe, Vince Lyzinski, Minh Tang, 2017, 2017 IEEE International Conference on Data Mining Workshops (ICDMW).

Two-sample Testing on Latent Distance Graphs With Unknown Link Functions

S. Lahiri, M. Tang, Yiran Wang, 2020, 2008.01038.

Perturbation Analysis of Randomized SVD and its Applications to High-dimensional Statistics

Yichi Zhang, M. Tang, 2022, ArXiv.

Limit results for distributed estimation of invariant subspaces in multiple networks inference and PCA

M. Tang, Runbing Zheng, 2022, 2206.04306.

Eigenvalues of Stochastic Blockmodel Graphs and Random Graphs with Low-Rank Edge Probability Matrices

A. Athreya, M. Tang, J. Cape, 2021, Sankhya A.

Exact Recovery of Community Structures Using DeepWalk and Node2vec

Minh Tang, Yichi Zhang, M. Tang, 2021, 2101.07354.

Nonparametric Two-Sample Hypothesis Testing for Random Graphs with Negative and Repeated Eigenvalues.

C. Priebe, Minh Tang, Joshua Agterberg, 2020, 2012.09828.

On spectral embedding performance and elucidating network structure in stochastic blockmodel graphs

Carey E. Priebe, Minh Tang, Joshua Cape, 2018, Network Science.

Locality Statistics for Anomaly Detection in Time Series of Graphs

Heng Wang, Carey E. Priebe, Youngser Park, 2013, IEEE Transactions on Signal Processing.

On Latent Position Inference from Doubly Stochastic Messaging Activities

Carey E. Priebe, Jordan Yoder, Minh Tang, 2012, Multiscale Model. Simul..

M. Trosset, Minh Tang, John Koo, 2021, J. Comput. Graph. Stat..

Numerical Tolerance for Spectral Decompositions of Random Matrices and Applications to Network Inference

C. Priebe, V. Lyzinski, A. Athreya, 2022, J. Comput. Graph. Stat..

Classification of high-dimensional data with spiked covariance matrix structure pdf

Yin-Jen Chen, Minh Tang, Yingyi Chen, 2021, ArXiv.

Consistency of random-walk based network embedding algorithms pdf

Yichi Zhang, Minh Tang, Yichi Zhang, 2021, ArXiv.

A Comparison of Graph Embedding Methods for Vertex Nomination

Carey E. Priebe, Ming Sun, Minh Tang, 2012, 2012 11th International Conference on Machine Learning and Applications.

On Two Distinct Sources of Nonidentifiability in Latent Position Random Graph Models

C. Priebe, Minh Tang, Joshua Agterberg, 2020, 2003.14250.

Empirical Bayes Estimation for the Stochastic Blockmodel

Carey E. Priebe, Daniel L. Sussman, Shakira Suwan, 2014, 1405.6070.

Valid two‐sample graph testing via optimal transport Procrustes and multiscale graph correlation with applications in connectomics

Carey E. Priebe, Joshua T. Vogelstein, Jesus Arroyo, 2019, 1911.02741.

Ieee Transactions on Pattern Analysis and Machine Intelligence (tpami) Attribute Fusion in a Latent Process Model for Time Series of Graphs Appendix Proofs of Some Stated Results

N. H. Lee, C. Priebe, Youngser Park, 2022 .

Improving Power of 2-Sample Random Graph Tests with Applications in Connectomics

C. Priebe, J. Vogelstein, Minh Tang, 2019 .