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20162026
most citedClustering in graphs and hypergraphs with categorical edge labels

62 citations · 81 across the 22 of their papers we have counts for

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17 papers · 1 filter

cs.DS2026

An Improved Combinatorial Algorithm for Edge-Colored Clustering in Hypergraphs

Seongjune Han, Nate Veldt

Many complex systems and datasets are characterized by multiway interactions of different categories, and can be modeled as edge-colored hypergraphs. We focus on clustering such da…

cs.DS2026

Better Learning-Augmented Spanning Tree Algorithms via Metric Forest Completion

Nate Veldt, Thomas Stanley, Benjamin W. Priest +5

We present improved learning-augmented algorithms for finding an approximate minimum spanning tree (MST) for points in an arbitrary metric space. Our work follows a recent framewor…

cs.DS2025

A Simple and Fast -approximation for Constrained Correlation Clustering

Nate Veldt

In Constrained Correlation Clustering, the goal is to cluster a complete signed graph in a way that minimizes the number of negative edges inside clusters plus the number of positi…

cs.DS2025

The Densest SWAMP problem: subhypergraphs with arbitrary monotonic partial edge rewards

Vedangi Bengali, Nikolaj Tatti, Iiro Kumpulainen +2

We consider a generalization of the densest subhypergraph problem where nonnegative rewards are given for including partial hyperedges in a dense subhypergraph. Prior work addresse…

cs.DS2025

Edge-Colored Clustering in Hypergraphs: Beyond Minimizing Unsatisfied Edges

Alex Crane, Thomas Stanley, Blair D. Sullivan +1

We consider a framework for clustering edge-colored hypergraphs, where the goal is to cluster (equivalently, to color) objects based on the primary type of multiway interactions th…

cs.DS2025

Approximate Tree Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees

Nate Veldt, Thomas Stanley, Benjamin W. Priest +4

Finding a minimum spanning tree (MST) for points in an arbitrary metric space is a fundamental primitive for hierarchical clustering and many other ML tasks, but this takes $Ω(…