= Rprop
{wiki=Rprop}
Rprop, or Resilient Backpropagation, is a variant of the backpropagation algorithm used for training artificial neural networks. It was designed to address some of the issues associated with standard gradient descent methods, particularly the sensitivity to the scale of the parameters and the need for careful tuning of the learning rate. \#\#\# Key features of Rprop: 1. **Individual Learning Rates**: Rprop maintains a separate learning rate for each weight in the network.
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