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. Most ...

In this course, you’ll learn theoretical foundations of optimization methods used for training deep machine learning models. Why does gradient descent work? Specifically, what can we guarantee about ...

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

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...

A method for establishing a berth schedule consisting of berthing times and berthing positions of containerships in port container terminals is addressed in this paper. Each vessel requires a specific ...

SIAM Journal on Numerical Analysis, Vol. 52, No. 2 (2014), pp. 1050-1075 (26 pages) The signed volume function for polyhedra can be generalized to a mean volume function for volume elements by ...

A new technical paper titled “Learning in Log-Domain: Subthreshold Analog AI Accelerator Based on Stochastic Gradient Descent” was published by researchers at Imperial College London. “The rapid ...