8 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.DS2026
Approximate Dual Separation for the Cluster LP: a 1.387 approximation for Correlation Clustering
David García-Soriano, Antoine Schohn
We give a deterministic -approximation for correlation clustering on complete graphs, improving the previous best factor of of Cao et al. (STOC'24). Our first…
cs.DS2020
Finding Densest -Connected Subgraphs
Francesco Bonchi, David García-Soriano, Atsushi Miyauchi +1
Dense subgraph discovery is an important graph-mining primitive with a variety of real-world applications. One of the most well-studied optimization problems for dense subgraph dis…
cs.DS2020★ 8 cited
Query-Efficient Correlation Clustering
David García-Soriano, Konstantin Kutzkov, Francesco Bonchi +1
Correlation clustering is arguably the most natural formulation of clustering. Given n objects and a pairwise similarity measure, the goal is to cluster the objects so that, to the…