Gradient descent is an optimization algorithm that refines a machine learning model's parameters to create a more accurate model. The goal is to reduce a model's ...

Optimization problems can be tricky, but they make the world work better. These kinds of questions, which strive for the best way of doing something, are absolutely everywhere. Your phone’s GPS ...

Dr. James McCaffrey of Microsoft Research explains stochastic gradient descent (SGD) neural network training, specifically implementing a bio-inspired optimization technique called differential ...

Your institution does not have access to this book on JSTOR. Try searching on JSTOR for other items related to this book. Gradient-Based Methods for Deterministic Continuous Optimization Chapter One ...

The most widely used technique for finding the largest or smallest values of a math function turns out to be a fundamentally difficult computational problem. Many aspects of modern applied research ...

A backpropagation algorithm, or backward propagation of errors, is an algorithm that's used to help train neural network models. The algorithm adjusts the network's weights to minimize any gaps -- ...