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 algorithm, which is based on the derivation of a cost function, is used to optimize the connecting weights, but neural networks have a lot of other knobs to turn.

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.

Still, it was in the 1970s that the backpropagation algorithm was first proposed and independently developed by David Rumelhart, Geoffrey Hinton, and Ronald Williams at the University of California, ...

A new technical paper titled “The backpropagation algorithm implemented on spiking neuromorphic hardware” was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal ...

Neural networks using the backpropagation algorithm were biologically “unrealistic in almost every respect” he said. For one thing, neurons mostly send information in one direction.

Hopfield’s work is not particularly in use today, but the backpropagation algorithm (co-invented by Hinton) has had a tremendous impact on many different sciences and technologies. This is ...