New Error Bounds for Solomonoff Prediction
نویسندگان
چکیده
منابع مشابه
New Error Bounds for Solomonoff Prediction
Solomonoff sequence prediction is a scheme to predict digits of binary strings without knowing the underlying probability distribution. We call a prediction scheme informed when it knows the true probability distribution of the sequence. Several new relations between universal Solomonoff sequence prediction and informed prediction and general probabilistic prediction schemes will be proved. Amo...
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Structured prediction tasks in machine learning involve the simultaneous prediction of multiple labels. This is typically done by maximizing a score function on the space of labels, which decomposes as a sum of pairwise elements, each depending on two specific labels. Intuitively, the more pairwise terms are used, the better the expected accuracy. However, there is currently no theoretical acco...
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Algorithmic information theory gives an idealized notion of compressibility, that is often presented as an objective measure of simplicity. It is suggested at times that Solomonoff prediction, or algorithmic information theory in a predictive setting, can deliver an argument to justify Occam’s razor. This paper explicates the relevant argument, and, by converting it into a Bayesian framework, r...
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Solomonoff’s uncomputable universal prediction scheme ξ allows to predict the next symbol xk of a sequence x1...xk−1 for any Turing computable, but otherwise unknown, probabilistic environment μ. This scheme will be generalized to arbitrary environmental classes, which, among others, allows the construction of computable universal prediction schemes ξ. Convergence of ξ to μ in a conditional mea...
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ژورنال
عنوان ژورنال: Journal of Computer and System Sciences
سال: 2001
ISSN: 0022-0000
DOI: 10.1006/jcss.2000.1743