Offline to online conversion
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Hutter, Marcus
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Springer Verlag
Abstract
We consider the problem of converting offline estimators into an online predictor or estimator with small extra regret. Formally this is the problem of merging a collection of probability measures over strings of length 1,2,3,... into a single probability measure over infinite sequences. We describe various approaches and their pros and cons on various examples. As a side-result we give an elementary non-heuristic purely combinatoric derivation of Turing’s famous estimator. Our main technical contribution is to determine the computational complexity of online estimators with good guarantees in general.
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Algorithmic Learning Theory: 25th International Conference, ALT 2014, Bled, Slovenia, October 8-10, 2014. Proceedings
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Open Access
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Restricted until
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