AI RESEARCH
Prediction Under Imperfect Compression: A Theory of Approximate MDL
arXiv CS.LG
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ArXi:2606.04834v1 Announce Type: new Minimum Description Length (MDL) formalizes the principle of Occam's razor by optimizing the total description length: $L(\mathrm{model})+L(\mathrm{data} \ | \ \mathrm{model})$. For sequential prediction, the MDL method repeatedly selects a model with a minimum objective score of the observed prefix for the next step prediction. Classical MDL prediction theory shows that exact optimization of the MDL objective indeed provides a strong compression guarantee that s reliable prediction.