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    block this user Matteo Gagliolo

    Post Doctorate

    CoMo, VUB, Brussels

    A Neural Network Model for Inter-problem Adaptive Online Time Allocation

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    One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive model of algorithm performance needed for task often requires long training times. We address the problem in an online fashion, running multiple algorithms in parallel on a sequence of tasks, continually updating their relative priorities according to a neural model that maps their current state to the expected time to the solution. The model itself is updated at the end of each task, based on the actual performance of each algorithm. Censored sampling allows us to train the model effectively, without need of additional exploration after each tasks solution. We present a preliminary experiment in which this new inter-problem technique learns to outperform a previously proposed intra-problem heuristic.

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    Description

    Title : A Neural Network Model for Inter-problem Adaptive Online Time Allocation
    Author(s) : Matteo Gagliolo, Jürgen Schmidhuber
    Abstract : One aim of Meta-learning techniques is to minimize the time needed for problem solving, and the effort of parameter hand-tuning, by automating algorithm selection. The predictive model of algorithm performance needed for task often requires long training times. We address the problem in an online fashion, running multiple algorithms in parallel on a sequence of tasks, continually updating their relative priorities according to a neural model that maps their current state to the expected time to the solution. The model itself is updated at the end of each task, based on the actual performance of each algorithm. Censored sampling allows us to train the model effectively, without need of additional exploration after each tasks solution. We present a preliminary experiment in which this new inter-problem technique learns to outperform a previously proposed intra-problem heuristic.
    Subject : unspecified
    Area : Other
    Language : English
    Year : 2005

    Affiliations CoMo, VUB, Brussels
    Editors : W Lodzis Law Duch, Et Al.
    Conference_title : Artificial Neural Networks Formal Models and Their Applications ICANN 2005 15th International Conference Warsaw Poland September 1115 2005 Proceedings Part 2
    Volume : 3697
    Publisher : Springer
    Pages : 7-12
    Url : http://como.vub.ac.be/~mgagliol/Gagliolo05ICANN.pdf
    Doi : 10.1007/11550907_2

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