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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7070))

Abstract

Meta-learning can be seen as alternating the construction of configuration of learning machines for validation, scheduling of such tasks and the meta-knowledge collection.

This article presents a few modifications of complexity measures and their application in advising to scheduling test tasks—validation tasks of learning machines in meta-learning process. Additionally some comments about their optimality in context of meta-learning are presented.

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Jankowski, N. (2013). Complexity Measures for Meta-learning and Their Optimality. In: Dowe, D.L. (eds) Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence. Lecture Notes in Computer Science, vol 7070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44958-1_15

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  • DOI: https://doi.org/10.1007/978-3-642-44958-1_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-44957-4

  • Online ISBN: 978-3-642-44958-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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