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An Introduction to Compression-Based Machine Learning

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Any lossless compression algorithm (like gzip) may be converted into a machine learning method, via either Normalized Compression Distance or the Minimum Description Length principle. Any auto-regressive model may be converted into a lossless compression method via entropy coding. This seemingly circular dependence has unrealized potential in modern artificial intelligence and machine learning, and we survey and formalize the various strategies that have been used to leverage compression for machine learning. We introduce and empirically validate a design framework for compression-based ML, fi

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Evidence & attribution

First collected: 2026-09-23T14:01:59.594Z. This is not the publication date.