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Teaching Randomized Learners

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Learning Theory (COLT 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4005))

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Abstract

The present paper introduces a new model for teaching randomized learners. Our new model, though based on the classical teaching dimension model, allows to study the influence of various parameters such as the learner’s memory size, its ability to provide or to not provide feedback, and the influence of the order in which examples are presented. Furthermore, within the new model it is possible to investigate new aspects of teaching like teaching from positive data only or teaching with inconsistent teachers.

Furthermore, we provide characterization theorems for teachability from positive data for both ordinary teachers and inconsistent teachers with and without feedback.

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© 2006 Springer-Verlag Berlin Heidelberg

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Balbach, F.J., Zeugmann, T. (2006). Teaching Randomized Learners. In: Lugosi, G., Simon, H.U. (eds) Learning Theory. COLT 2006. Lecture Notes in Computer Science(), vol 4005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11776420_19

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  • DOI: https://doi.org/10.1007/11776420_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35294-5

  • Online ISBN: 978-3-540-35296-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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