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Found 6 papers, 5 papers with code
Approximate Nearest Neighbor Search with Window Filters
We define and investigate the problem of $\textit{c-approximate window search}$: approximate nearest neighbor search where each point in the dataset has a numeric label, and the goal is to find nearest neighbors to queries within arbitrary label ranges.
PECANN: Parallel Efficient Clustering with Graph-Based Approximate Nearest Neighbor Search
In particular, we study variants of density peaks clustering, a popular type of algorithm that has been shown to work well in practice.
ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
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.
Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering
Our approach is based on generating a well-separated pair decomposition followed by using Kruskal's minimum spanning tree algorithm and bichromatic closest pair computations.
Theoretically-Efficient and Practical Parallel DBSCAN
The DBSCAN method for spatial clustering has received significant attention due to its applicability in a variety of data analysis tasks.
GraphIt - A High-Performance DSL for Graph Analytics
This paper introduces GraphIt, a new DSL for graph computations that generates fast implementations for algorithms with different performance characteristics running on graphs with different sizes and structures.
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