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Product Quantization (PQ) is a technique for compressing high-dimensional vectors into compact codes, enabling efficient approximate nearest neighbor (ANN) search in vector databases. PQ reduces memory footprint and search time, making it a foundational algorithm for large-scale vector search systems.

Spectral Hashing is a method for approximate nearest neighbor search that uses spectral graph theory to generate compact binary codes, often applied in vector databases to enhance retrieval efficiency on large-scale, high-dimensional data.