Minh Tang

Zhang, Y., & Tang, M. (2024). A Theoretical Analysis of DeepWalk and Node2vec for Exact Recovery of Community Structures in Stochastic Blockmodels. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 46(2), 1065–1078. https://doi.org/10.1109/TPAMI.2023.3327631

Du, X., & Tang, M. (2023). Hypothesis testing for equality of latent positions in random graphs. BERNOULLI, 29(4), 3221–3254. https://doi.org/10.3150/22-BEJ1581

Rubin-Delanchy, P., Cape, J., Tang, M., & Priebe, C. E. (2022, June 3). A statistical interpretation of spectral embedding: The generalised random dot product graph. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY. https://doi.org/10.1111/rssb.12509

Tang, M., Cape, J., & Priebe, C. E. (2022). Asymptotically efficient estimators for stochastic blockmodels: The naive MLE, the rank-constrained MLE, and the spectral estimator. BERNOULLI, 28(2), 1049–1073. https://doi.org/10.3150/21-BEJ1376

Athreya, A., Lubberts, Z., Priebe, C. E., Park, Y., Tang, M., Lyzinski, V., … Lewis, B. W. (2022, July 18). Numerical Tolerance for Spectral Decompositions of Random Matrices and Applications to Network Inference. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS. https://doi.org/10.1080/10618600.2022.2082972

Koo, J., Tang, M., & Trosset, M. W. (2022, June 25). Popularity Adjusted Block Models are Generalized Random Dot Product Graphs. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS. https://doi.org/10.1080/10618600.2022.2081576

Chung, J., Varjavand, B., Arroyo-Relion, J., Alyakin, A., Agterberg, J., Tang, M., … Vogelstein, J. T. (2022). Valid two-sample graph testing via optimal transport Procrustes and multiscale graph correlation with applications in connectomics. STAT, 11(1). https://doi.org/10.1002/sta4.429

Zheng, R., Lyzinski, V., Priebe, C. E., & Tang, M. (2022, May 13). Vertex Nomination Between Graphs via Spectral Embedding and Quadratic Programming. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS. https://doi.org/10.1080/10618600.2022.2060238

Athreya, A., Cape, J., & Tang, M. (2021, November 3). Eigenvalues of Stochastic Blockmodel Graphs and Random Graphs with Low-Rank Edge Probability Matrices. SANKHYA-SERIES A-MATHEMATICAL STATISTICS AND PROBABILITY. https://doi.org/10.1007/s13171-021-00268-x

Athreya, A., Tang, M., Park, Y., & Priebe, C. E. (2021). On Estimation and Inference in Latent Structure Random Graphs. STATISTICAL SCIENCE, 36(1), 68–88. https://doi.org/10.1214/20-STS787

Li, G., Tang, M., Charon, N., & Priebe, C. (2020). Central limit theorems for classical multidimensional scaling. ELECTRONIC JOURNAL OF STATISTICS, 14(1), 2362–2394. https://doi.org/10.1214/20-EJS1720

Cape, J., Tang, M., & Priebe, C. E. (2019). On spectral embedding performance and elucidating network structure in stochastic blockmodel graphs. NETWORK SCIENCE, 7(3), 269–291. https://doi.org/10.1017/nws.2019.23