On Theorem 2.3 in "Prediction, Learning, and Games" by Cesa-Bianchi and Lugosi

Details On Theorem 2.3 in "Prediction, Learning, and Games" by Cesa-Bianchi and Lugosi On Theorem 2.3 in "Prediction, Learning, and Games" by Cesa-Bianchi and Lugosi

2010-11-25

arxiv.org/abs/1011.5668v1

Computer Science

Learning

3 pages; excerpt from arXiv:1005.1918, simplified and rewritten using the notation of the monograph by Cesa-Bianchi and Lugosi

Scientific paper

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.

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