Weighted MinHash implementation on CUDA (multi-gpu).
-
Updated
Nov 29, 2023 - C++
Weighted MinHash implementation on CUDA (multi-gpu).
High Dimensional Approximate Near(est) Neighbor
Query-Aware LSH for Approximate NNS (PVLDB 2015 and VLDBJ 2017)
fast kernel evaluation in high dimensions via hashing
A framework for index based similarity search.
Query-Aware LSH for Approximate NNS (In-Memory Version of QALSH)
distill large scale web page text
CMU Foreground/Background Similarity Server from DARPA MEMEX
Nearest neighbor search. Methods: LSH, hypercube, and exhaustive search. C++
Memory Version of RQALSH for Furthest Neighbor Search (TKDE 2017)
Reverse Query-Aware LSH for Furthest Neighbor Search (TKDE 2017)
Implementation and survey of similarity search methods that rely on dimensionality reduction (e.g. LSH), D-dimensional vector clustering
LSH and Hypercube algorithms for Approximate Nearest Neighbor. Centroid based clustering using Lloyd's and reverse assignment algorithms.
A deduplication lib built Over [SIMHASH](https://github.com/yanyiwu/simhash).
Add a description, image, and links to the lsh topic page so that developers can more easily learn about it.
To associate your repository with the lsh topic, visit your repo's landing page and select "manage topics."