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Adaptive Online Prediction by Following the Perturbed Leader

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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

Description

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

Citation

URI

http://hdl.handle.net/1885/57847

Collections

ANU Research Publications

Source

Journal of Machine Learning Research

Type

Journal article

Book Title

Entity type

Access Statement

Open Access

License Rights

DOI

Restricted until

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01_Hutter_Adaptive_Online_Prediction_by_2005.pdf (329.61 KB)

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