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Nice! For completeness, a link to some of the original classification-by-compression work: https://www.cs.waikato.ac.nz/~eibe/pubs/Frank_categorization.full.ps.gz …
Thanks! I had been looking around a bit for similar papers but haven't found much. It seems well-known in the statistical compression community. Indeed, I have to thank Christopher Mattern (from @DeepMindAI) for mentioning this over drinks three years ago as a fun fact/idea 
You can get 45% accuracy on binarized MNIST using class-wise compression and counting bits 
No 
