Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

James McCaffrey explains the common neural network training technique known as the back-propagation algorithm.

The standard “back-propagation” training technique for deep neural networks requires matrix multiplication, an ideal workload for GPUs. With SLIDE, Shrivastava, Chen and Medini turned neural network ...

“Deep neural networks (DNNs) are typically trained using the conventional stochastic gradient descent (SGD) algorithm. However, SGD performs poorly when applied to train networks on non-ideal analog ...

On a more basic level, [Gigante] did just that, teaching a neural network to play a basic driving game with a genetic algorithm. The game consists of a basic top-down 2D driving game.

Dropout training is a relatively new algorithm which appears to be highly effective for improving the quality of neural network predictions. It's not yet widely implemented in neural network API ...

Neural networks (NNs) are one of the most widely used techniques for pattern classification. Owing to the most common back-propagation training algorithm of NN being extremely computationally ...

Neural networks hold this promise, but scientists must use them with caution – or risk discovering that they have solved the wrong problem entirely, writes Janelle Shane Generation game: Images of ...