@inproceedings{
kunze2024practical,
title={Practical Shuffle Coding},
author={Julius Kunze and Daniel Severo and Jan-Willem van de Meent and James Townsend},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=m2DaXpCoIi}
}
We present a general method for lossless compression of unordered data structures, including multisets and graphs. It is a variant of shuffle coding that is many orders of magnitude faster than the original and enables 'one-shot' compression of single unordered objects. Our method achieves state-of-the-art compression rates on various large-scale network graphs at speeds of megabytes per second, efficiently handling even a multi-gigabyte plain graph with one billion edges. We release an implementation that can be easily adapted to different data types and statistical models.
Practical Shuffle Coding
Julius Kunze Daniel Severo Jan-Willem van de Meent James Townsend