Search Control Techniques for Planning. - Minh Tang; Amol Dattatraya Mali (ICTAI, 2003)

Variants of A* for Planning. - Minh Tang; Amol Dattatraya Mali (ECAI, 2004)

State-space Planning with Variants of A*. - Amol Dattatraya Mali; Minh Tang (Int. J. Artif. Intell. Tools, 2006)

Generating Functions and the Solutions of Full History Recurrence Equations. - Minh Tang (Electron. Notes Discret. Math., 2007)

A Comparison of Graph Embedding Methods for Vertex Nomination. - Ming Sun; Minh Tang; Carey E. Priebe (ICMLA (1), 2012)

Inference in time series of graphs using locality statistics. - Heng Wang; Minh Tang; Carey E. Priebe; Youngser Park (GlobalSIP, 2013)

Metric Space Structures for Computational Anatomy. - Jianqiao Feng; Xiaoying Tang 001; Minh Tang; Carey E. Priebe; Michael I. Miller (MLMI, 2013)

On Latent Position Inference from Doubly Stochastic Messaging Activities. - Nam H. Lee; Jordan Yoder; Minh Tang; Carey E. Priebe (Multiscale Model. Simul., 2013)

Generalized canonical correlation analysis for disparate data fusion. - Ming Sun; Carey E. Priebe; Minh Tang (Pattern Recognit. Lett., 2013)

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 J. Matrix Anal. Appl., 2013)

Attribute Fusion in a Latent Process Model for Time Series of Graphs. - Minh Tang; Youngser Park; Nam H. Lee; Carey E. Priebe (IEEE Trans. Signal Process., 2013)

Generalized canonical correlation analysis for classification. - Cencheng Shen; Ming Sun; Minh Tang; Carey E. Priebe (J. Multivar. Anal., 2014)

Consistent Latent Position Estimation and Vertex Classification for Random Dot Product Graphs. - Daniel L. Sussman; Minh Tang; Carey E. Priebe (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Locality Statistics for Anomaly Detection in Time Series of Graphs. - Heng Wang; Minh Tang; Youngser Park; Carey E. Priebe (IEEE Trans. Signal Process., 2014)

Path-Cost Bounds for Parameterized Centralized Variants of A* for Static and Certain Environments. - Amol Dattatraya Mali; Minh Tang (Int. J. Artif. Intell. Tools, 2016)

A Central Limit Theorem for an Omnibus Embedding of Multiple Random Dot Product Graphs. - Keith D. Levin; Avanti Athreya; Minh Tang; Vince Lyzinski; Carey E. Priebe (ICDM Workshops, 2017)

A statistical interpretation of spectral embedding: the generalised random dot product graph. - Patrick Rubin-Delanchy; Carey E. Priebe; Minh Tang; Joshua Cape (CoRR, 2017)

Statistical Inference on Random Dot Product Graphs: a Survey. - Avanti Athreya; Donniell E. Fishkind; Minh Tang; Carey E. Priebe; Youngser Park; Joshua T. Vogelstein; Keith D. Levin; Vince Lyzinski; Yichen Qin; Daniel L. Sussman (J. Mach. Learn. Res., 2017)

Community Detection and Classification in Hierarchical Stochastic Blockmodels. - Vince Lyzinski; Minh Tang; Avanti Athreya; Youngser Park; Carey E. Priebe (IEEE Trans. Netw. Sci. Eng., 2017)

The eigenvalues of stochastic blockmodel graphs. - Minh Tang (CoRR, 2018)

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 (CoRR, 2018)

On spectral embedding performance and elucidating network structure in stochastic blockmodel graphs. - Joshua Cape; Minh Tang; Carey E. Priebe (Netw. Sci., 2019)

Learning 1-Dimensional Submanifolds for Subsequent Inference on Random Dot Product Graphs. - Michael W. Trosset; Mingyue Gao; Minh Tang; Carey E. Priebe (CoRR, 2020)

Consistency of random-walk based network embedding algorithms. - Yichi Zhang; Minh Tang (CoRR, 2021)

Classification of high-dimensional data with spiked covariance matrix structure. - Yin-Jen Chen; Minh Tang (CoRR, 2021)

Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings. - Keith D. Levin; Fred Roosta; Minh Tang; Michael W. Mahoney; Carey E. Priebe (J. Mach. Learn. Res., 2021)

Perturbation Analysis of Randomized SVD and its Applications to High-dimensional Statistics. - Yichi Zhang; Minh Tang (CoRR, 2022)

Adversarial contamination of networks in the setting of vertex nomination: a new trimming method. - Sheyda Peyman; Minh Tang; Vince Lyzinski (CoRR, 2022)

Vertex Nomination Between Graphs via Spectral Embedding and Quadratic Programming. - Runbing Zheng; Vince Lyzinski; Carey E. Priebe; Minh Tang (J. Comput. Graph. Stat., 2022)

Motif-Based Exploratory Data Analysis for State-Backed Platform Manipulation on Twitter. - Khuzaima Hameed; Rob Johnston; Brent Younce; Minh Tang; Alyson G. Wilson (ICWSM, 2023)

Numerical Tolerance for Spectral Decompositions of Random Matrices and Applications to Network Inference. - Avanti Athreya; Zachary Lubberts; Carey E. Priebe; Youngser Park; Minh Tang; Vince Lyzinski; Michael J. Kane; Bryan W. Lewis (J. Comput. Graph. Stat., 2023)

Popularity Adjusted Block Models are Generalized Random Dot Product Graphs. - John Koo; Minh Tang; Michael W. Trosset (J. Comput. Graph. Stat., 2023)

Regression for matrix-valued data via Kronecker products factorization. - Yin-Jen Chen; Minh Tang (CoRR, 2024)

A Theoretical Analysis of DeepWalk and Node2vec for Exact Recovery of Community Structures in Stochastic Blockmodels. - Yichi Zhang; Minh Tang (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Out-of-Sample Embedding with Proximity Data: Projection versus Restricted Reconstruction. - Michael W. Trosset; Kaiyi Tan; Minh Tang; Carey E. Priebe (CoRR, 2025)