activity
20132023
most citedUnifying Sparsest Cut, Cluster Deletion, and Modularity Clustering Objectives with Correlation Clustering

69 citations · 85 across the 16 of their papers we have counts for

collaborators
Showing 2019Show all

2 papers · 1 filter

cs.CC2019

Graph Clustering in All Parameter Regimes

Junhao Gan, David F. Gleich, Nate Veldt +2

Resolution parameters in graph clustering represent a size and quality trade-off. We address the task of efficiently solving a parameterized graph clustering objective for all valu…

cs.SI2019

Learning Resolution Parameters for Graph Clustering

Nate Veldt, David F. Gleich, Anthony Wirth

Finding clusters of well-connected nodes in a graph is an extensively studied problem in graph-based data analysis. Because of its many applications, a large number of distinct gra…