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Optimality of universal Bayesian sequence prediction for general loss and alphabet

Hutter, Marcus


Various optimality properties of universal sequence predictors based on Bayes-mixtures in general, and Solomonoff's prediction scheme in particular, will be studied. The probability of observing xt at time t, given past observations x1...xt-1 can be computed with the chain rule if the true generating distribution μ of the sequences x 1x2x3... is known. If μ is unknown, but known to belong to a countable or continuous class M one can base ones prediction on the Bayes-mixture ℰ defined as...[Show more]

CollectionsANU Research Publications
Date published: 2003
Type: Journal article
Source: Journal of Machine Learning Research
DOI: 10.1162/1532443041827952


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