1 citations · 1 across the 4 of their papers we have counts for
6 papers
Chamfer-Linkage for Hierarchical Agglomerative Clustering
Kishen N Gowda, Willem Fletcher, MohammadHossein Bateni +4
Hierarchical Agglomerative Clustering (HAC) is a widely-used clustering method based on repeatedly merging the closest pair of clusters, where inter-cluster distances are determine…
Aggregating maximal cliques in real-world graphs
Noga Alon, Sabyasachi Basu, Shweta Jain +3
Maximal clique enumeration is a fundamental graph mining task, but its utility is often limited by computational intractability and highly redundant output. To address these challe…
Parallel Hierarchical Agglomerative Clustering in Low Dimensions
MohammadHossein Bateni, Laxman Dhulipala, Willem Fletcher +4
Hierarchical Agglomerative Clustering (HAC) is an extensively studied and widely used method for hierarchical clustering in based on repeatedly merging the closest p…
Efficient Centroid-Linkage Clustering
MohammadHossein Bateni, Laxman Dhulipala, Willem Fletcher +4
We give an efficient algorithm for Centroid-Linkage Hierarchical Agglomerative Clustering (HAC), which computes a -approximate clustering in roughly time. We ob…
It's Hard to HAC with Average Linkage!
MohammadHossein Bateni, Laxman Dhulipala, Kishen N Gowda +3
Average linkage Hierarchical Agglomerative Clustering (HAC) is an extensively studied and applied method for hierarchical clustering. Recent applications to massive datasets have d…
TeraHAC: Hierarchical Agglomerative Clustering of Trillion-Edge Graphs
Laxman Dhulipala, Jason Lee, Jakub Łącki +1
We introduce TeraHAC, a -approximate hierarchical agglomerative clustering (HAC) algorithm which scales to trillion-edge graphs. Our algorithm is based on a new approach to…