Gradient descent algorithms are widely considered the primary choice for optimizing deep learning models. However, they often require adjusting various hyperparameters, like the learning rate, among ...

Distributed stochastic gradient descent (SGD) has attracted considerable recent attention due to its potential for scaling computational resources, reducing training time, and helping protect user ...