Improving the Backpropagation Algorithm with Consequentialism Weight Updates over Mini-Batches

11 Mar 2020Naeem PaeedehKamaledin Ghiasi-Shirazi

Least mean squares (LMS) is a particular case of the backpropagation (BP) algorithm applied to single-layer neural networks with the mean squared error (MSE) loss. One drawback of the LMS is that the instantaneous weight update is proportional to the square of the norm of the input vector... (read more)

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