Optimality of universal Bayesian prediction for general loss and alphabet
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 x1x2x3.... is known. If μ is unknown, but known to belong to a countable or continuous class Μ one can base ones prediction on the Bayes-mixture ξ defined as a...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of Machine Learning Research|
|Hutter Optimality of Universal Bayesian Sequence Prediction 2003.pdf||330.6 kB||Adobe PDF|
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