Master algorithms for active experts problems based on increasing loss values
We specify an experts algorithm with the following characteristics: (a) it uses only feedback from the actions actually chosen (bandit setup), (b) it can be applied with countably infinite expert classes, and (c) it copes with losses that may grow in time appropriately slowly. We prove loss bounds against an adaptive adversary. From this, we obtain master algorithms for ``active...[Show more]
|Collections||ANU Research Publications|
|Book Title:||Proceedings of the 14th Dutch-Belgium Conference on Machine Learning Benelearn'05|
|Poland and Hutter Master Algorithms for Active Experts Problems 2005.pdf||219.37 kB||Adobe PDF|
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