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Probabilistic Routing for Graph-Based Approximate Nearest Neighbor Search
Feb. 20, 2024, 5:41 a.m. | Kejing Lu, Chuan Xiao, Yoshiharu Ishikawa
cs.LG updates on arXiv.org arxiv.org
Abstract: Approximate nearest neighbor search (ANNS) in high-dimensional spaces is a pivotal challenge in the field of machine learning. In recent years, graph-based methods have emerged as the superior approach to ANNS, establishing a new state of the art. Although various optimizations for graph-based ANNS have been introduced, they predominantly rely on heuristic methods that lack formal theoretical backing. This paper aims to enhance routing within graph-based ANNS by introducing a method that offers a probabilistic …
abstract anns approximate nearest neighbor art arxiv challenge cs.ai cs.cv cs.db cs.ds cs.lg graph graph-based machine machine learning pivotal routing search spaces state state of the art type
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