112 citations · 370 across the 54 of their papers we have counts for
6 papers · 1 filter
Parallel Batch-Dynamic d-Trees
Rahul Yesantharao, Yiqiu Wang, Laxman Dhulipala +1
d-trees are widely used in parallel databases to support efficient neighborhood/similarity queries. Supporting parallel updates to d-trees is therefore an important operation…
Theoretically and Practically Efficient Parallel Nucleus Decomposition
Jessica Shi, Laxman Dhulipala, Julian Shun
This paper studies the nucleus decomposition problem, which has been shown to be useful in finding dense substructures in graphs. We present a novel parallel algorithm that is effi…
Scalable Community Detection via Parallel Correlation Clustering
Jessica Shi, Laxman Dhulipala, David Eisenstat +2
Graph clustering and community detection are central problems in modern data mining. The increasing need for analyzing billion-scale data calls for faster and more scalable algorit…
Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time
Laxman Dhulipala, David Eisenstat, Jakub Łącki +2
We study the widely used hierarchical agglomerative clustering (HAC) algorithm on edge-weighted graphs. We define an algorithmic framework for hierarchical agglomerative graph clus…
ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
Shangdi Yu, Yiqiu Wang, Yan Gu +2
This paper studies the hierarchical clustering problem, where the goal is to produce a dendrogram that represents clusters at varying scales of a data set. We propose the ParChain…
Parallel Batch-Dynamic Algorithms for -Core Decomposition and Related Graph Problems
Quanquan C. Liu, Jessica Shi, Shangdi Yu +2
Maintaining a -core decomposition quickly in a dynamic graph has important applications in network analysis. The main challenge for designing efficient exact algorithms is that…