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VALUETOOLS 2014
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    VALUETOOLS

    8th International Conference on Performance Evaluation Methodologies and Tools

    The theory or approachability, introduced by Blackwell in 1956, provides fundamental results on guaranteed performance regions in repeated games with vector-valued payoffs. These results, which have been applied in theoretical work on learning in games, have recently been the subject of renewed int…

    The theory or approachability, introduced by Blackwell in 1956, provides fundamental results on guaranteed performance regions in repeated games with vector-valued payoffs. These results, which have been applied in theoretical work on learning in games, have recently been the subject of renewed interest in the machine learning community due to their close connection with on-line learning algorithms. In this lecture, we will first review the basic approachability framework, outline its inter-connection with no-regret learning, and describe some applications to routing and scheduling. We will then describe some advances that include to new approachability algorithms, and their application to generalized no-regret problems.

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    Editor(s): Moshe Haviv (Hebrew University of Jerusalem, Israel), William Knottenbelt ( Imperial College London, United Kindom), Lorenzo Maggi (Create-Net Research Association, Italy) and Daniele Miorandi (Create-Net Research Association, U-Hopper s.r.l. Italy)
    Publisher
    ICST
    ISBN
    978-1-63190-057-0
    Conference dates
    9th–11th Dec 2014
    Location
    Bratislava, Slovakia
    Appeared in EUDL
    2015-02-19
    Appears in
    ACM Digital Library

    Copyright © 2015–2025 ICST

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      Research Article in 8th International Conference on Performance Evaluation Methodologies and Tools

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      Research Article in 8th International Conference on Performance Evaluation Methodologies and Tools

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      Research Article in 8th International Conference on Performance Evaluation Methodologies and Tools

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