5 papers
PiPNN: Ultra-Scalable Graph-Based Nearest Neighbor Indexing
Tobias Rubel, Richard Wen, Laxman Dhulipala +3
The fastest indexes for Approximate Nearest Neighbor Search today are also the slowest to build: graph-based methods like HNSW and Vamana achieve state-of-the-art query performance…
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…
JAG: Joint Attribute Graphs for Filtered Nearest Neighbor Search
Haike Xu, Guy Blelloch, Laxman Dhulipala +3
Despite filtered nearest neighbor search being a fundamental task in modern vector search systems, the performance of existing algorithms is highly sensitive to query selectivity a…
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…
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…