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Learning by MDL

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Part of the book series: Progress in Computer Science and Applied Logic ((PCS,volume 14))

Abstract

Machine learning has been formalized as the problem of estimating a conditional distribution as the ‘concept’ to be learned. The learning algorithm is based upon the MDL (Minimum Description Length) principle. The asymptotically optimal learning rate is determined for a typical example.

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© 1996 Birkhäuser Boston

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Rissanen, J., Yu, B. (1996). Learning by MDL. In: Kueker, D.W., Smith, C.H. (eds) Learning and Geometry: Computational Approaches. Progress in Computer Science and Applied Logic, vol 14. Birkhäuser Boston. https://doi.org/10.1007/978-1-4612-4088-4_1

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  • DOI: https://doi.org/10.1007/978-1-4612-4088-4_1

  • Publisher Name: Birkhäuser Boston

  • Print ISBN: 978-1-4612-8646-2

  • Online ISBN: 978-1-4612-4088-4

  • eBook Packages: Springer Book Archive

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