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- W2044794688 abstract "On-line learning in layered perceptrons is often hampered by plateaus in the time dependence of the performance. Studies on backpropagation in networks with a small number of input units have revealed that correlations between subsequently presented patterns shorten the length of such plateaus. We show how to extend the statistical mechanics framework to quantitatively check the effect of correlations on learning in networks with a large number of input units. The surprisingly compact description we obtain makes it possible to derive properties of on-learning with correlations directly from studies on on-line learning without correlations." @default.
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- W2044794688 date "1997-07-21" @default.
- W2044794688 modified "2023-09-26" @default.
- W2044794688 title "Learning in two-layered networks with correlated examples" @default.
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- W2044794688 doi "https://doi.org/10.1088/0305-4470/30/14/011" @default.
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