FusionANNS architecture by Bing Tian et al. for billion-scale ANN search using CPU/GPU cooperation.
https://arxiv.org/search/cs?query=FusionANNS
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SPANN: Highly-efficient Billion-scale Approximate Nearest Neighbor Search
Highly-efficient billion-scale approximate nearest neighbor search algorithm introduced by Chen et al. Focuses on scalability and performance for large datasets in high-dimensional spaces. Relevant for vector database indexing techniques.
Exploring the Meaningfulness of Nearest Neighbor Search in High-Dimensional Space
Research paper by Chen et al. examining the meaningfulness of nearest neighbor search in high-dimensional spaces. Analyzes limitations and implications for vector similarity search. Key for understanding ANN effectiveness.
GleanVec: Accelerating vector search with minimalist nonlinear dimensionality reduction
Paper by Tepper et al. proposing GleanVec, a method to accelerate vector search using minimalist nonlinear dimensionality reduction. Improves efficiency for high-dimensional vector queries.
iDEC: Indexable Distance Estimating Codes for Approximate Nearest Neighbor Search
iDEC by Gong et al. for approximate nearest neighbor search using indexable distance estimating codes. VLDB Endowment 13.9 (2020).
Subspace Collision: An Efficient and Accurate Framework for High-dimensional Approximate Nearest Neighbor Search
Framework by Wei et al. for high-dimensional ANN search using subspace collision techniques. Offers efficiency and accuracy improvements for vector databases.
Distance Comparison Operators for Approximate Nearest Neighbor Search: Exploration and Benchmark
Explores and benchmarks distance comparison operators for ANN. arXiv preprint arXiv:2403.13491 (2024) by Zeyu Wang et al. Aids in vector search optimization.
