2026-07-20T05:27:55Z https://drops.dagstuhl.de/oai

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Recent Results in Universal and Non-Universal Induction Poland, Jan Bayesian learning MDL stochastic model selection prediction with expert advice universal learning Solomonoff induction We present and relate recent results in prediction based on countable classes of either probability (semi-)distributions or base predictors. Learning by Bayes, MDL, and stochastic model selection will be considered as instances of the first category. In particular, we will show how analog assertions to Solomonoff's universal induction result can be obtained for MDL and stochastic model selection. The second category is based on prediction with expert advice. We will present a recent construction to define a universal learner in this framework. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Jan Poland 2006 Is Part Of Dagstuhl Seminar Proceedings, Volume 6051, Kolmogorov Complexity and Applications (2006) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.06051.12 urn:nbn:de:0030-drops-6355 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06051.12 eng https://creativecommons.org/licenses/by/4.0/legalcode