118 citations · 438 across the 49 of their papers we have counts for
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stat.ML2022
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…
stat.ME2022
Lost in the Shuffle: Testing Power in the Presence of Errorful Network Vertex Labels
Ayushi Saxena, Vince Lyzinski
Two-sample network hypothesis testing is an important inference task with applications across diverse fields such as medicine, neuroscience, and sociology. Many of these testing me…
stat.ML2022
Clustered Graph Matching for Label Recovery and Graph Classification
Zhirui Li, Jesus Arroyo, Konstantinos Pantazis +1
Given a collection of vertex-aligned networks and an additional label-shuffled network, we propose procedures for leveraging the signal in the vertex-aligned collection to recover…