Comment by woliveirajr | Hacker News Reader

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Comment by woliveirajr | Hacker News Reader

There is Compression done by Prediction by partial matching [0]

There is the Kolmogorov Complexity [1], Normalized Information Distance [2] and Normalized compression distance [3] that correlates those.

Finally, there's the Pre-Big Bang Informational Compression and the Delayed Release of Antimatter [4]

All big {rabbit/black} holes to lose some time, if you have any.

[0] https://en.wikipedia.org/wiki/Prediction_by_partial_matching

[1] https://en.wikipedia.org/wiki/Kolmogorov_complexity

[2] https://homepages.cwi.nl/~paulv/papers/chapter08.pdf

[3] https://en.wikipedia.org/wiki/Normalized_compression_distanc...

[4] https://philarchive.org/rec/GREPBI

I'll add Minimum Description Length to the mix. Under certain definitions and conditions, it equals the Bayesian Information Criterion plus an extra term, which I consider a very interesting result in this "two faces of the same coin" perspective.

https://philarchive.org/rec/GRETIO-35

https://quantum-journal.org/papers/q-2020-07-20-301/

This is exactly why I think they are one and the same. It's relatively trivial to just plop a (lossy) machine learned markov chain instead of one learned (perfectly) from the data into PPM. With zero changes to the rest of the algorithm.

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