Active Learning with Statistical Models

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Active Learning with Statistical Models (1995)

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by David A. Cohn , Zoubin Ghahramani , Michael I. Jordan

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679 - 10 self

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@MISC{Cohn95activelearning,
    author = {David A. Cohn and Zoubin Ghahramani and Michael I. Jordan},
    title = {Active Learning with Statistical Models},
    year = {1995}
}

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Abstract

For manytypes of learners one can compute the statistically "optimal" way to select data. We review how these techniques have been used with feedforward neural networks [MacKay, 1992# Cohn, 1994]. We then showhow the same principles may be used to select data for two alternative, statistically-based learning architectures: mixtures of Gaussians and locally weighted regression. While the techniques for neural networks are expensive and approximate, the techniques for mixtures of Gaussians and locally weighted regression are both efficient and accurate.

Keyphrases

active learning statistical model weighted regression feedforward neural network optimal way statistically-based learning architecture neural network

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