Prediction, Learning, Uniform Convergence, and Scale-Sensitive Dimensions
نویسندگان
چکیده
منابع مشابه
Prediction, Learning, Uniform Convergence, and Scale-Sensitive Dimensions
We present a new general-purpose algorithm for learning classes of [0, 1]-valued functions in a generalization of the prediction model and prove a general upper bound on the expected absolute error of this algorithm in terms of a scale-sensitive generalization of the Vapnik dimension proposed by Alon, Ben-David, Cesa-Bianchi, and Haussler. We give lower bounds implying that our upper bounds can...
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Convergence Conditions for Frequency Sensitive Competitive Learning
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ژورنال
عنوان ژورنال: Journal of Computer and System Sciences
سال: 1998
ISSN: 0022-0000
DOI: 10.1006/jcss.1997.1557