Adaptive Online Prediction by Following the Perturbed Leader
Date
2005
Authors
Hutter, Marcus
Poland, Jan
Journal Title
Journal ISSN
Volume Title
Publisher
MIT Press
Abstract
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 part
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Keywords
Keywords: Algorithms; Boundary value problems; Expert systems; Hierarchical systems; Learning systems; Online systems; Perturbation techniques; Probability; Adaptive adversary; Adaptive learning rate; Expected and high probability bounds; Follow the perturbed leade Adaptive adversary; Adaptive learning rate; Expected and high probability bounds; Follow the perturbed leader; General alphabet and loss; General weights; Hierarchy of experts; Online sequential prediction; Prediction with expert advice
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Source
Journal of Machine Learning Research
Type
Journal article
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Access Statement
Open Access
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