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Found 5 papers, 4 papers with code
Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs
For a certain choice of parameters it is also related to our hypergraph objective.
Learning Resolution Parameters for Graph Clustering
We begin by formalizing the notion of a parameter fitness function, which measures how well a fixed input clustering approximately solves a generalized clustering objective for a specific resolution parameter value.
A Projection Method for Metric-Constrained Optimization
We outline a new approach for solving optimization problems which enforce triangle inequalities on output variables.
Unifying Sparsest Cut, Cluster Deletion, and Modularity Clustering Objectives with Correlation Clustering
Graph clustering, or community detection, is the task of identifying groups of closely related objects in a large network.
Data Structures and Algorithms Social and Information Networks
Correlation Clustering with Low-Rank Matrices
In this paper we explore how to solve the correlation clustering objective exactly when the data to be clustered can be represented by a low-rank matrix.
