Entropy Coding of Unordered Data Structures
Machine Learning
2024-08-19 v1 Data Structures and Algorithms
Information Theory
math.IT
Abstract
We present shuffle coding, a general method for optimal compression of sequences of unordered objects using bits-back coding. Data structures that can be compressed using shuffle coding include multisets, graphs, hypergraphs, and others. We release an implementation that can easily be adapted to different data types and statistical models, and demonstrate that our implementation achieves state-of-the-art compression rates on a range of graph datasets including molecular data.
Cite
@article{arxiv.2408.08837,
title = {Entropy Coding of Unordered Data Structures},
author = {Julius Kunze and Daniel Severo and Giulio Zani and Jan-Willem van de Meent and James Townsend},
journal= {arXiv preprint arXiv:2408.08837},
year = {2024}
}
Comments
Published at ICLR 2024