A Reproducibility Study of Variance-Aware Quantization

We propose a reproducibility study of Variance-Aware Quantization (VAQ). We propose an implementation in Rust. Moreover, we also experimentally compare the performance of VAQ with the other state-of-the-art methods, in particular, Product Quantization and Optimized Product Quantization. Finally, we propose a method to improve the performance of VAQ by using the HNSW algorithm, a popular—graph-based k-nearest neighbors search method.

Publication Details

Journal
Electronic Theses and Dissertations Repository (University of Pisa)
Published
2024-10-06
Primary Topic
Reproductive biology and impacts on aquatic species
Type
article
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article

A Reproducibility Study of Variance-Aware Quantization

Electronic Theses and Dissertations Repository (University of Pisa)
Reproductive biology and impacts on aquatic species
article

A Reproducibility Study of Variance-Aware Quantization

article en

Abstract

We propose a reproducibility study of Variance-Aware Quantization (VAQ). We propose an implementation in Rust. Moreover, we also experimentally compare the performance of VAQ with the other state-of-the-art methods, in particular, Product Quantization and Optimized Product Quantization. Finally, we propose a method to improve the performance of VAQ by using the HNSW algorithm, a popular—graph-based k-nearest neighbors search method.

Electronic Theses and Dissertations Repository (University of Pisa)
Openalex Percentile: Top 50%
Reproductive biology and impacts on aquatic species
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A Reproducibility Study of Variance-Aware Quantization · Electronic Theses and Dissertations Repository (University of Pisa) (2024) | TGRS Research Map | TGRS