Exponentiated gradient descent applied to backpropagation is proposed for a multilayer feedforward neural network. The learning rules for changing weights in the output layer as well the hidden layer ...

Gradients for each layer are calculated, and the weights and biases are updated using a gradient descent algorithm. 5)Repeat steps 3) and 4) until the predetermined number of iterations is reached.

Artificial Neural network, backpropogation algorithm using gradient descent to train a Feed-Forward Neural Network (1 hidden layer)-- Classification - Classify Flowers (IRIS data set).

Here, we propose a hardware implementation of the backpropagation algorithm that progressively updates each layer using in situ stochastic gradient descent, avoiding this storage requirement.

The tools are applied to the setting of neural network image classifiers, where we generate novel, on-manifold data samples and implement a projected gradient descent algorithm for on-manifold ...

Find out why backpropagation and gradient descent are key to prediction in machine learning, then get started with training a simple neural network using gradient descent and Java code.