especially when you can't find a suitable training method. The convergence rate of radial basis function neural network will be slow when the gradient descent algorithm is used for the training of ...

Hardware architectures composed of resistive cross-point device arrays can provide significant power and speed benefits for deep neural network training workloads using stochastic gradient descent ...

This paper mainly explains Quantification Aware Training. The basic concept of quantification aware training and the basic algorithm are introduced to make the reader have a basic understanding of ...

The approaches are similar but can produce very different results. The general consensus among neural network researchers is that when using the back-propagation training algorithm, using the online ...

He built a program that will get Mario through an entire level of Super Mario World – Donut Plains 1 – using neural networks ... as the training data it is given. [SethBling]’s algorithm ...

However, training deep learning models ... In most discussions, deep learning means using deep neural networks. There are, however, a few algorithms that implement deep learning using other ...

Directly training spiking neural networks (SNNs) has remained challenging due to complex neural dynamics and intrinsic non-differentiability in firing functions. The well-known backpropagation through ...