Minh Tang

IEEE Trans. Pattern Anal. Mach. Intell., February, 2024

Regression for matrix-valued data via Kronecker products factorization.

[BibT_eX]

[DOI]

Yin-Jen Chen

CoRR, 2024

2023

Popularity Adjusted Block Models are Generalized Random Dot Product Graphs.

[BibT_eX]

[DOI]

John Koo

Michael W. Trosset

J. Comput. Graph. Stat., January, 2023

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

[BibT_eX]

[DOI]

J. Comput. Graph. Stat., January, 2023

Motif-Based Exploratory Data Analysis for State-Backed Platform Manipulation on Twitter.

[BibT_eX]

[DOI]

Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, 2023

2022

Vertex Nomination Between Graphs via Spectral Embedding and Quadratic Programming.

[BibT_eX]

[DOI]

J. Comput. Graph. Stat., October, 2022

Adversarial contamination of networks in the setting of vertex nomination: a new trimming method.

[BibT_eX]

[DOI]

Sheyda Peyman

Vince Lyzinski

CoRR, 2022

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

[BibT_eX]

[DOI]

Yichi Zhang

CoRR, 2022

2021

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

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

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

[BibT_eX]

[DOI]

Yin-Jen Chen

CoRR, 2021

Consistency of random-walk based network embedding algorithms.

[BibT_eX]

[DOI]

Yichi Zhang

CoRR, 2021

2020

Learning 1-Dimensional Submanifolds for Subsequent Inference on Random Dot Product Graphs.

[BibT_eX]

[DOI]

CoRR, 2020

2019

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

[BibT_eX]

[DOI]

Joshua Cape

Netw. Sci., 2019

2018

On a 'Two Truths' Phenomenon in Spectral Graph Clustering.

[BibT_eX]

[DOI]

CoRR, 2018

The eigenvalues of stochastic blockmodel graphs.

[BibT_eX]

[DOI]

CoRR, 2018

2017

Community Detection and Classification in Hierarchical Stochastic Blockmodels.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Sci. Eng., 2017

Statistical Inference on Random Dot Product Graphs: a Survey.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2017

A statistical interpretation of spectral embedding: the generalised random dot product graph.

[BibT_eX]

[DOI]

Patrick Rubin-Delanchy

Joshua Cape

CoRR, 2017

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

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

2016

Path-Cost Bounds for Parameterized Centralized Variants of A* for Static and Certain Environments.

[BibT_eX]

[DOI]

Int. J. Artif. Intell. Tools, 2016

2014

Locality Statistics for Anomaly Detection in Time Series of Graphs.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2014

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

[BibT_eX]

[DOI]

Daniel L. Sussman

IEEE Trans. Pattern Anal. Mach. Intell., 2014

Generalized canonical correlation analysis for classification.

[BibT_eX]

[DOI]

J. Multivar. Anal., 2014

2013

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

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2013

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

[BibT_eX]

[DOI]

SIAM J. Matrix Anal. Appl., 2013

Generalized canonical correlation analysis for disparate data fusion.

[BibT_eX]

[DOI]

Ming Sun

Pattern Recognit. Lett., 2013

On Latent Position Inference from Doubly Stochastic Messaging Activities.

[BibT_eX]

[DOI]

Multiscale Model. Simul., 2013

Metric Space Structures for Computational Anatomy.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning in Medical Imaging - 4th International Workshop, 2013

Inference in time series of graphs using locality statistics.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013

2012

A Comparison of Graph Embedding Methods for Vertex Nomination.

[BibT_eX]

[DOI]

Ming Sun

Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

2007

Generating Functions and the Solutions of Full History Recurrence Equations.

[BibT_eX]

[DOI]

Electron. Notes Discret. Math., 2007

2006

State-space Planning with Variants of A*.

[BibT_eX]

[DOI]

Int. J. Artif. Intell. Tools, 2006

2004

Variants of A* for Planning.

[BibT_eX]

Proceedings of the 16th Eureopean Conference on Artificial Intelligence, 2004

2003

Search Control Techniques for Planning.

[BibT_eX]

[DOI]