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Almeida–Pineda recurrent backpropagation is a technique used for training recurrent neural networks (RNNs). It was introduced by J. Almeida and M. Pineda in a paper published in the late 1980s. This method is an extension of the standard backpropagation algorithm, which is typically used for feedforward neural networks.

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