Similarity search on neighbor's graphs with automatic Pareto optimal performance and minimum expected quality setups based on hyperparameter optimization
Information Retrieval
2022-01-21 v1 Artificial Intelligence
Abstract
This manuscript introduces an autotuned algorithm for searching nearest neighbors based on neighbor graphs and optimization metaheuristics to produce Pareto-optimal searches for quality and search speed automatically; the same strategy is also used to produce indexes that achieve a minimum quality. Our approach is described and benchmarked with other state-of-the-art similarity search methods, showing convenience and competitiveness.
Cite
@article{arxiv.2201.07917,
title = {Similarity search on neighbor's graphs with automatic Pareto optimal performance and minimum expected quality setups based on hyperparameter optimization},
author = {Eric S. Tellez and Guillermo Ruiz},
journal= {arXiv preprint arXiv:2201.07917},
year = {2022}
}
Comments
Submitted to a peer reviewed journal