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Authors: Olivier Teytaud 1 ; Sylvain Gelly 1 and Jérémie Mary 2

Affiliations: 1 TAO (Inria, Univ. Paris-Sud, UMR CNRS-8623), France ; 2 TAO (Inria, Univ. Paris-Sud, UMR CNRS-8623); Grappa (Inria Univ. Lille), France

Keyword(s): Intelligent Control Systems and Optimization, Machine learning in control applications, Active learning.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Machine Learning in Control Applications

Abstract: We study active learning as a derandomized form of sampling. We show that full derandomization is not suitable in a robust framework, propose partially derandomized samplings, and develop new active learning methods (i) in which expert knowledge is easy to integrate (ii) with a parameter for the exploration/exploitation dilemma (iii) less randomized than the full-random sampling (yet also not deterministic). Experiments are performed in the case of regression for value-function learning on a continuous domain. Our main results are (i) efficient partially derandomized point sets (ii) moderate-derandomization theorems (iii) experimental evidence of the importance of the frontier (iv) a new regression-specific user-friendly sampling tool less-robust than blind samplers but that sometimes works very efficiently in large dimensions. All experiments can be reproduced by downloading the source code and running the provided command line.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Teytaud, O.; Gelly, S. and Mary, J. (2007). ACTIVE LEARNING IN REGRESSION, WITH APPLICATION TO STOCHASTIC DYNAMIC PROGRAMMING. In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-972-8865-82-5; ISSN 2184-2809, SciTePress, pages 198-205. DOI: 10.5220/0001645701980205

@conference{icinco07,
author={Olivier Teytaud. and Sylvain Gelly. and Jérémie Mary.},
title={ACTIVE LEARNING IN REGRESSION, WITH APPLICATION TO STOCHASTIC DYNAMIC PROGRAMMING},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2007},
pages={198-205},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001645701980205},
isbn={978-972-8865-82-5},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - ACTIVE LEARNING IN REGRESSION, WITH APPLICATION TO STOCHASTIC DYNAMIC PROGRAMMING
SN - 978-972-8865-82-5
IS - 2184-2809
AU - Teytaud, O.
AU - Gelly, S.
AU - Mary, J.
PY - 2007
SP - 198
EP - 205
DO - 10.5220/0001645701980205
PB - SciTePress