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On delayed prediction of individual sequences

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2 Author(s)
Weinberger, M.J. ; Hewlett Packard Labs., Palo Alto, CA, USA ; Ordentlich, E.

We investigate a prediction scenario in which the predictor is forced to make a decision a number of steps in advance, with incomplete information. For finite action and observation spaces, it is shown that the strategy that minimizes the worst-case regret with respect to the Bayes envelope is obtained through sub-sampling of the sequence of observations. The result extends to the case of logarithmic loss.

Published in:

Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on

Date of Conference: