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Product Quantization for compressed distance computation
Splits D-dimensional vectors into M subspaces of D/M dimensions each, then quantizes each subspace independently using k-means (k=256 centroids).
Structs§
- Product
Quantizer - Product Quantizer with M subspaces, 256 centroids each (1 byte per subspace)