This article describes the backpropagation algorithm, a basic neural network, ... One of the earliest neural network models was the perceptron, an invention of F. Rosenblat in 1962.

Geoffrey Hinton, professor at the University of Toronto and engineering fellow at Google Brain, recently published a paper on the Forward-Forward algorithm (FF), a technique for training neural networ ...

A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI. Every time a human or machine learns how ...

In early December, dozens of alternatives to traditional backpropagation were proposed during a workshop at the NeurIPS 2020 conference, which took place virtually.

A new technical paper titled “Hardware implementation of backpropagation using progressive gradient descent for in situ training of multilayer neural networks” was published by researchers at ...

Of course, Rosenblatt’s Mark 1 Perceptron could barely see a triangle, let alone the future. But in terms of foreshadowing an era when computers would learn like never before, it indeed offered ...

Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material.