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General loss bounds for universal sequence prediction

Hutter, Marcus

Description

The Bayesian framework is ideally suited for induction problems. The probability of observing xk at time k, given past observations x1...xk-1 can be computed with Bayes' rule if the true distribution µ of the sequences x1x2x3... is known. The problem, however, is that in many cases one does not even have a reasonable estimate of the true distribution. In order to overcome this problem a universal distribution ß is defined as a weighted sum of distributions µi in M, where M is any countable set...[Show more]

CollectionsANU Research Publications
Date published: 2001
Type: Conference paper
URI: http://hdl.handle.net/1885/15159

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