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  Prediction and dimension (2002) [10 citations — 2 self]

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by Lance Fortnow, Jack H. Lutz
Journal of Computer and System Sciences
http://www.neci.nj.nec.com/homepages/fortnow/papers/./predict.ps
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Abstract:

Abstract. Given a set X of sequences over a nite alphabet, we investigate the following three quantities. (i) The feasible predictability of X is the highest success ratio that a polynomial-time randomized predictor can achieve on all sequences in X. (ii) The deterministic feasible predictability of X is the highest success ratio that a polynomial-time deterministic predictor can achieve on all sequences in X. (iii) The feasible dimension of X is the polynomial-time eectivization of the classical Hausdor dimension (\fractal dimension") of X. Predictability is known to be stable in the sense that the feasible predictability of X[Y is always the minimum of the feasible predictabilities of X and Y. We show that deterministic predictability also has this property if X and Y are computably presentable. We show that deterministic predictability coincides with predictability on singleton sets. Our main theorem states that the feasible dimension of X is bounded above by the maximum entropy of the predictability of X and bounded below by the segmented self-information of the predictability of X, and that these bounds are tight. 1

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