118 citations · 202 across the 17 of their papers we have counts for
17 papers
Minimax rates for latent position estimation in the generalized random dot product graph
Hao Yan, Keith Levin
Latent space models play an important role in the modeling and analysis of network data. Under these models, each node has an associated latent point in some (typically low-dimensi…
Predicting Responses from Weighted Networks with Node Covariates in an Application to Neuroimaging
Daniel Kessler, Keith Levin, Elizaveta Levina
We consider the setting where many networks are observed on a common node set, and each observation comprises edge weights of a network, covariates observed at each node, and an ov…
Fast Generation of Exchangeable Sequence of Clusters Data
Keith Levin, Brenda Betancourt
Recent advances in Bayesian models for random partitions have led to the formulation and exploration of Exchangeable Sequences of Clusters (ESC) models. Under ESC models, it is the…
Vertex Nomination in Richly Attributed Networks
Keith Levin, Carey E. Priebe, Vince Lyzinski
Vertex nomination is a lightly-supervised network information retrieval task in which vertices of interest in one graph are used to query a second graph to discover vertices of int…
Matrix Means and a Novel High-Dimensional Shrinkage Phenomenon
Asad Lodhia, Keith Levin, Elizaveta Levina
Many statistical settings call for estimating a population parameter, most typically the population mean, based on a sample of matrices. The most natural estimate of the population…
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings
Keith Levin, Fred Roosta, Minh Tang +2
Graph embeddings, a class of dimensionality reduction techniques designed for relational data, have proven useful in exploring and modeling network structure. Most dimensionality r…