mingyu-hkustgz/RESQ
High-Ratio Vector Quantization
When you have massive datasets of high-dimensional vectors and need to quickly find the most similar items (approximate k-nearest neighbors), this project helps you do it much faster and with less memory. It takes in your existing vector data and outputs a highly compressed index, enabling rapid similarity searches. Data scientists, machine learning engineers, and researchers working with large-scale vector databases would find this useful.
Use this if you need to perform very fast approximate nearest neighbor searches on extremely large collections of high-dimensional data while significantly reducing the memory footprint.
Not ideal if your dataset is small, or if you require perfect (exact) nearest neighbor search accuracy rather than approximate results.
Stars
10
Forks
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Language
C++
License
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Category
Last pushed
Feb 03, 2026
Commits (30d)
0
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