In this work, we propose a local learning algorithm that significantly reduces computational complexity as well as improves training performance. Our algorithm combines multiple consecutive layers ...

In this regard, Hinton proposes the FF algorithm as an alternative to backpropagation for neural network learning. The FF algorithm is inspired by Boltzmann machines (Hinton and Sejnowski, 1986) and ...

BP algorithm can be used not only for multilayer feedforward neural networks, but also for other types of neural networks. PS: In this programming, Sigmoid function (f = 1/ (1+exp (-z))) is used as ...

The backpropagation algorithm needs to be implemented in our code to evaluate the gradient. Note that the number of input nodes in the neural network here is three, corresponding to the two principal ...

Correspondence of the phases for different learning algorithms: Back-propagation, Equilibrium Propagation (our algorithm), Contrastive Hebbian Learning (and Boltzmann Machine Learning) and ...

Several models have been proposed that approximate the backpropagation algorithm with local synaptic plasticity, but these models require complex external control over the network or relatively ...

Multi-layered neural architectures that implement learning require elaborate mechanisms for symmetric backpropagation of errors that are biologically implausible. Here the authors propose a simple ...