8 citations · 13 across the 5 of their papers we have counts for
5 papers
Adversarial contamination of networks in the setting of vertex nomination: a new trimming method
Sheyda Peyman, Minh Tang, Vince Lyzinski
As graph data becomes more ubiquitous, the need for robust inferential graph algorithms to operate in these complex data domains is crucial. In many cases of interest, inference is…
Signed and Unsigned Partial Information Decompositions of Continuous Network Interactions
Jesse Milzman, Vince Lyzinski
We investigate the partial information decomposition (PID) framework as a tool for edge nomination. We consider both the and PIDs, fr…
On the Consistency of the Likelihood Maximization Vertex Nomination Scheme: Bridging the Gap Between Maximum Likelihood Estimation and Graph Matching
Vince Lyzinski, Keith Levin, Donniell E. Fishkind +1
Given a graph in which a few vertices are deemed interesting a priori, the vertex nomination task is to order the remaining vertices into a nomination list such that there is a con…
Graph Matching: Relax at Your Own Risk
Vince Lyzinski, Donniell Fishkind, Marcelo Fiori +3
Graph matching---aligning a pair of graphs to minimize their edge disagreements---has received wide-spread attention from both theoretical and applied communities over the past sev…
A semiparametric two-sample hypothesis testing problem for random dot product graphs
Minh Tang, Avanti Athreya, Daniel L. Sussman +2
Two-sample hypothesis testing for random graphs arises naturally in neuroscience, social networks, and machine learning. In this paper, we consider a semiparametric problem of two-…