Towards a Model for LSH
Databases
2021-05-12 v1 Data Structures and Algorithms
Machine Learning
Abstract
As data volumes continue to grow, clustering and outlier detection algorithms are becoming increasingly time-consuming. Classical index structures for neighbor search are no longer sustainable due to the "curse of dimensionality". Instead, approximated index structures offer a good opportunity to significantly accelerate the neighbor search for clustering and outlier detection and to have the lowest possible error rate in the results of the algorithms. Locality-sensitive hashing is one of those. We indicate directions to model the properties of LSH.
Cite
@article{arxiv.2105.05130,
title = {Towards a Model for LSH},
author = {Li Wang},
journal= {arXiv preprint arXiv:2105.05130},
year = {2021}
}
Comments
arXiv admin note: text overlap with arXiv:2103.01888