Learn how to differentiate between backpropagation and reinforcement learning algorithms, their inputs, outputs, learning processes, scalability, and generalization.

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The Forward-Forward algorithm (FF) is comparable in speed to backpropagation but has the advantage that it can be used when the precise details of the forward computation are unknown.

The backpropagation (BP) algorithm allows multilayer feedforward neural networks to learn input-output mappings from training samples. Due to the nonlinear modeling power of such networks, the learned ...

Standard neural network based on back-propagation learning algorithm has some faults, such as low learning rate, instability, and long learning time. In this paper, we introduce trust-field method and ...

Backpropagation of errors, or backprop, is a widely used algorithm in training artificial neural networks using gradient descent for supervised learning. The basics of continuous backpropagation were ...