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Add to EdgeOn Theorem 2.3 in "Prediction, Learning, and Games" by Cesa-Bianchi and Lugosi
Paper and Code
Nov 25, 2010
The note presents a modified proof of a loss bound for the exponentially weighted average forecaster with time-varying potential. The regret term of the algorithm is upper-bounded by sqrt{n ln(N)} (uniformly in n), where N is the number of experts and n is the number of steps.
* 3 pages; excerpt from arXiv:1005.1918, simplified and rewritten using
the notation of the monograph by Cesa-Bianchi and Lugosi
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