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Intro
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Classroom Contents
Graph-Based Approximate Nearest Neighbors and HNSW
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- 1 Intro
- 2 Vector Search
- 3 Exhaustive Search
- 4 Approximate Search
- 5 Many ANNS Algorithms
- 6 Graph algorithms
- 7 Advantages of graph algorithm
- 8 Delaunay graphs and Voronoi diagrams
- 9 Problems with Delaunay graphs
- 10 Delaunay Graph Subgraphs
- 11 Relative neighborhood graph (RNG)
- 12 Skip-lists analogy
- 13 HNSW construction
- 14 Extension to memory-constrained scenarios
- 15 Using graphs a coarse quantizer (ivf-hnsw)
- 16 DiskANN
- 17 SPANN and HNSW-IF
- 18 Updates and deletions.
- 19 Benchmarking SQUAD
- 20 Benchmarking MSMARCO
- 21 Practical advice
