43 citations · 72 across the 19 of their papers we have counts for
7 papers · 1 filter
Flow-Based Local Graph Clustering with Better Seed Set Inclusion
Nate Veldt, Christine Klymko, David Gleich
Flow-based methods for local graph clustering have received significant recent attention for their theoretical cut improvement and runtime guarantees. In this work we present two i…
A Short Introduction to Local Graph Clustering Methods and Software
Kimon Fountoulakis, David F. Gleich, Michael W. Mahoney
Graph clustering has many important applications in computing, but due to the increasing sizes of graphs, even traditionally fast clustering methods can be computationally expensiv…
Correlation Clustering Generalized
David F. Gleich, Nate Veldt, Anthony Wirth
We present new results for LambdaCC and MotifCC, two recently introduced variants of the well-studied correlation clustering problem. Both variants are motivated by applications to…
Low rank methods for multiple network alignment
Huda Nassar, Georgios Kollias, Ananth Grama +1
Multiple network alignment is the problem of identifying similar and related regions in a given set of networks. While there are a large number of effective techniques for pairwise…
The HyperKron Graph Model for higher-order features
Nicole Eikmeier, Arjun S. Ramani, David F. Gleich
Graph models have long been used in lieu of real data which can be expensive and hard to come by. A common class of models constructs a matrix of probabilities, and samples an adja…
Computing tensor Z-eigenvectors with dynamical systems
Austin R. Benson, David F. Gleich
We present a new framework for computing Z-eigenvectors of general tensors based on numerically integrating a dynamical system that can only converge to a Z-eigenvector. Our motiva…