Adaptive online prediction by following the perturbed leader
When applying aggregating strategies to Prediction with Expert Advice (PEA), the learning rate must be adaptively tuned. The natural choice of √ complexity/current loss renders the analysis of Weighted Majority (WM) derivatives quite complicated. In particular, for arbitrary weights there have been no results proven so far. The analysis of the alternative Follow the Perturbed Leader (FPL) algorithm from Kalai and Vempala (2003) based on Hannan’s algorithm is easier. We derive loss bounds...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of Machine Learning Research|
|Hutter and Poland Adaptive Online Prediction 2005.pdf||187.12 kB||Adobe PDF|
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