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- W2145586232 abstract "We present an algorithm for the training of feedforward and recurrent neural networks. It detects internal representation conflicts and uses these conflicts in a constructive manner to add new neurons to the network. The advantages are twofold: (1) starting with a small network neurons are only allocated when required; (2) by detecting and resolving internal conflicts at an early stage learning time is reduced. Empirical results on two real-world problems substantiate the faster learning speed; when applied to the training of a recurrent network on a well researched sequence recognition task (the Reber grammar), training times are significantly less than previously reported." @default.
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- W2145586232 date "1993-11-29" @default.
- W2145586232 modified "2023-09-24" @default.
- W2145586232 title "Constructive Learning Using Internal Representation Conflicts" @default.
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