Implementation of an ANN index with locality-sensitive hashing in C++, for efficient vector lookup of nearest neighbors.
- LSH
- HyperCube
Hash Vectors with amplified hash functions and use Hash Table for storage.
Get approximate nearest neighbor - Or R-nearest neighbors, with M1 metric.
Hash Vectors with amplified hash functions and use Hyper Cube for storage. Get approximate nearest neighbor Or R-nearest neighbors, with M1 metric
- Grid LSH
- Projections
Curve Vectorization with Grid, then calling LSH for vectors on the vectorized curves. (Poor method)
Find all relevant traversals, and project the nearest traversals, and use LSH on vectorized traversals, instead of vectorizing Curves. (Better method for curves)
- Compilation
make all - Instructions for usage
./build/lsh.x
./build/hypercube.x