Entropy Coding of Unordered Data Structures

August 16, 2024 ยท Declared Dead ยท ๐Ÿ› International Conference on Learning Representations

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Authors Julius Kunze, Daniel Severo, Giulio Zani, Jan-Willem van de Meent, James Townsend arXiv ID 2408.08837 Category cs.LG: Machine Learning Cross-listed cs.DS, cs.IT Citations 6 Venue International Conference on Learning Representations Last Checked 5 months ago
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.
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