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Sample complexity for learning recurrent perceptron mappings

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Publication:4896826
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DOI10.1109/18.532888zbMath0858.68081OpenAlexW2156582723MaRDI QIDQ4896826

Bhaskar Das Gupta

Publication date: 22 October 1996

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/3db6753e4134f1cc9d47e768fd433c2f4719e4a3


zbMATH Keywords

probably approximately correct learningrecurrent perceptron classifiers


Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20)


Related Items (6)

Improving Generalization Capabilities of Dynamic Neural Networks ⋮ Complete controllability of continuous-time recurrent neural networks ⋮ Vapnik-Chervonenkis dimension of recurrent neural networks ⋮ The complexity of model classes, and smoothing noisy data ⋮ A learning result for continuous-time recurrent neural networks ⋮ Compressive sensing and neural networks from a statistical learning perspective







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