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    Supermartingales in prediction with expert advice

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    Authors
    Chernov, Alexey
    Kalnishkan, Yuri
    Zhdanov, Fedor
    Vovk, Vladimir
    Issue Date
    2010
    
    Metadata
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    Abstract
    The paper applies the method of defensive forecasting, based on the use of game-theoretic supermartingales, to prediction with expert advice. In the traditional setting of a countable number of experts and a finite number of outcomes, the Defensive Forecasting Algorithm is very close to the well-known Aggregating Algorithm. Not only the performance guarantees but also the predictions are the same for these two methods of fundamentally different nature. The paper also discusses a new setting where the experts can give advice conditional on the learner's future decision. Both the algorithms can be adapted to the new setting and give the same performance guarantees as in the traditional setting. Finally, an application of defensive forecasting to a setting with several loss functions is outlined.
    Citation
    Chernov, A., Kalnishkan, Y., Zhdanov, F. and Vovk, V., (2010) 'Supermartingales in prediction with expert advice' 411 (29-30):2647-2669 Theoretical Computer Science
    Publisher
    Elsevier
    Journal
    Theoretical Computer Science
    URI
    http://hdl.handle.net/10547/279178
    DOI
    10.1016/j.tcs.2010.04.003
    Additional Links
    http://linkinghub.elsevier.com/retrieve/pii/S0304397510001982
    Type
    Article
    Language
    en
    ISSN
    0304-3975
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.tcs.2010.04.003
    Scopus Count
    Collections
    Centre for Research in Distributed Technologies (CREDIT)

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