Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models
Given a graph with positive and negative edge labels, the correlation clustering problem
aims to cluster the nodes so to minimize the total number of between-cluster positive and …
aims to cluster the nodes so to minimize the total number of between-cluster positive and …
Clustering with Non-adaptive Subset Queries
Recovering the underlying clustering of a set $ U $ of $ n $ points by asking pair-wise same-
cluster queries has garnered significant interest in the last decade. Given a query $ S\subset …
cluster queries has garnered significant interest in the last decade. Given a query $ S\subset …
Min-CSPs on Complete Instances
Given a fixed arity $ k\geq 2$, Min-$ k $-CSP on complete instances involves a set of $ n $
variables $ V $ and one nontrivial constraint for every $ k $-subset of variables (so there are …
variables $ V $ and one nontrivial constraint for every $ k $-subset of variables (so there are …
Dynamic Correlation Clustering in Sublinear Update Time
We study the classic problem of correlation clustering in dynamic node streams. In this
setting, nodes are either added or randomly deleted over time, and each node pair is …
setting, nodes are either added or randomly deleted over time, and each node pair is …
Simultaneously Approximating All Norms for Massively Parallel Correlation Clustering
N Cao, S Li, J Ye - arXiv preprint arXiv:2410.09321, 2024 - arxiv.org
We revisit the simultaneous approximation model for the correlation clustering problem
introduced by Davies, Moseley, and Newman [DMN24]. The objective is to find a clustering …
introduced by Davies, Moseley, and Newman [DMN24]. The objective is to find a clustering …
Fully Dynamic Correlation Clustering: Breaking 3-Approximation
We study the classic correlation clustering in the dynamic setting. Given $ n $ objects and a
complete labeling of the object-pairs as either similar or dissimilar, the goal is to partition the …
complete labeling of the object-pairs as either similar or dissimilar, the goal is to partition the …
Recent Progress on Correlation Clustering: From Local Algorithms to Better Approximation Algorithms and Back (Invited Talk)
V Cohen-Addad - 32nd Annual European Symposium on …, 2024 - drops.dagstuhl.de
Correlation clustering is a classic model for clustering problems arising in machine learning
and data mining. Given a set of data elements represented as vertices of a graph and …
and data mining. Given a set of data elements represented as vertices of a graph and …