MIT researchers have developed a new machine-learning-based adaptive control algorithm for autonomous drones. The ...

In 1847, the French mathematician Augustin-Louis Cauchy was working on a suitably complicated example — astronomical calculations — when he pioneered a common method of optimization now known as ...

An evolutionary algorithm is any algorithm that loosely mimics ... DEO typically takes much longer to train a deep neural network than standard stochastic gradient descent (SGD) optimization ...

Why does gradient descent work? Specifically ... Programming assignments, typically involving training a neural network with a specified optimization method A final project with a presentation.

Gradient descent algorithms take the loss function and use partial derivatives to determine what each variable (weights and biases) in the network contributed to the loss value. It then moves ...

"There's something special about it." Gradient descent is an optimization approach for neural networks. A neural network has what are called weights that decide how much any single component of a ...