Entropy Coding of Unordered Data Structures
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
Text
Kunze et al. "Entropy Coding of Unordered Data Structures." International Conference on Learning Representations, 2024.Markdown
[Kunze et al. "Entropy Coding of Unordered Data Structures." International Conference on Learning Representations, 2024.](https://mlanthology.org/iclr/2024/kunze2024iclr-entropy/)BibTeX
@inproceedings{kunze2024iclr-entropy,
title = {{Entropy Coding of Unordered Data Structures}},
author = {Kunze, Julius and Severo, Daniel and Zani, Giulio and van de Meent, Jan-Willem and Townsend, James},
booktitle = {International Conference on Learning Representations},
year = {2024},
url = {https://mlanthology.org/iclr/2024/kunze2024iclr-entropy/}
}