 | This is a draft article. It is a work in progress open to editing by anyone. Please ensure core content policies are met before publishing it as a live Wikipedia article. Find sources: Google (books · news · scholar · free images · WP refs) · FENS · JSTOR · TWL Last edited by Cinder painter (talk | contribs) 5 months ago. (Update)
Finished drafting? or |
Product quantization (PQ) is a technique that decomposes high-dimensional vector spaces into a Cartesian product of low-dimensional subspaces, with each subspace quantized independently. This approach represents each vector by a compact code, enabling efficient distance estimation while significantly reducing memory usage. [1]
It is commonly used in approximate nearest neighbor search, like the Hierarchical navigable small world data structure.
- ^ "Product Quantization for Nearest Neighbor Search". hal.science. Retrieved 2025-03-21.