Abstract: The K-nearest neighbors (kNNs) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...
Vicinity is a light-weight, low-dependency vector store. It provides a simple and intuitive interface for nearest neighbor search, with support for different backends and evaluation. There are many ...
Abstract: This paper presents FastNN, a novel accelerator architecture for efficient K-Nearest Neighbors (KNN) search in point clouds. FastNN leverages a locality-sensitive E2LSH partitioning method ...
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