HNSW (Hierarchical Navigable Small World)

Graph-based algorithm for approximate nearest neighbor search where vertices represent vectors and edges are constructed heuristically. Foundation for HNSW with (poly/)logarithmic search complexity using greedy routing.

Graph-based indexing algorithm powering Microsoft's DiskANN. Uses flat graph structure with minimized search diameter for efficient disk-based nearest neighbor search with 40x GPU speedup available via NVIDIA cuVS.

Algorithmic technique for approximate nearest neighbor search in high-dimensional spaces using hash functions to map similar items to the same buckets with high probability.

Inverted File Index vector search algorithm that partitions high-dimensional vectors into clusters using k-means, enabling efficient nearest neighbor search by restricting searches to relevant clusters and dramatically reducing search space.

Family of algorithms trading perfect accuracy for speed in high-dimensional similarity search. Enables sub-linear query time with 90%+ recall on billion-scale datasets.

Clustering-based approximate nearest neighbor algorithm that partitions vector space into Voronoi cells. Fast search through coarse-to-fine strategy, often combined with Product Quantization (IVF-PQ).