collaborators

7 papers

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.CC2025

Improved Hardness and Approximations for Cardinality-Based Minimum - Cuts Problems in Hypergraphs

Florian Adriaens, Vedangi Bengali, Iiro Kumpulainen +2

In hypergraphs, an edge that crosses a cut (i.e., a bipartition of nodes) can be split in several ways, depending on how many nodes are placed on each side of the cut. A cardinalit…

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…