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Probably approximately correct learning / Inner product space / Polynomial / Function / Computational complexity theory / Machine learning / Supervised learning / Empirical risk minimization / Mathematics / Mathematical analysis / Computational learning theory


On Efficient Agnostic Learning of Linear Combinations of Basis Functions Wee Sun Lee Dept. of Systems Engineering, RSISE, Aust. National University, Canberra, ACT 0200, Australia.
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Document Date: 2005-03-22 04:23:34


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Graz / London / New York / /

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CNF / Cambridge University Press / Neural Networks / ACM Press / G. Let co / /

Country

Austria / Australia / /

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pence / IDR / /

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Reorganization / /

Facility

National University / Australian National University / /

IndustryTerm

probabilistic polynomial time algorithm / inner product / probabilistic algorithms / randomized algorithm / agnostic learning algorithm / weak learning algorithm / proper efficient agnostic learning algorithm / agnostic algorithm / proper efficient agnostic algorithm / learning algorithm / learning applications / /

Organization

Cambridge University / National University / Canberra / American Statistical Association / Robert C. Williamson Department of Engineering / Department of Systems Engineering / Institute for Theoretical Computer Science / Australian Research Council / Australian National University / /

Person

Peter L. Bartlett / Wee Sun Lee / Robert C. Williamson / Pascal Koiran / /

Position

HB / Prime Minister / B2R+ HB / Agnostic PAC learning Pm / 2R+ HB / /

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New York / /

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Machine Learning / Theoretical Computer Science / Journal of the American Statistical Association / /

Technology

learning algorithm / randomized algorithm / resulting algorithm / neural network / weak learning algorithm / agnostic learning algorithm / agnostic algorithm / Machine Learning / probabilistic polynomial time algorithm / Computer Algorithms / /

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