Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using C#

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

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...
JSTOR Daily

On Expected Error of Randomized Nyström Kernel Regression

Kernel methods are a class of machine learning algorithms which learn and discover patterns in a high (possibly infinite) dimensional feature space obtained by often nonlinear, possibly infinite ...
JSTOR Daily

Nonparametric Regression With Missing Outcomes Using Weighted Kernel Estimating Equations

We consider nonparametric regression of a scalar outcome on a covariate when the outcome is missing at random (MAR) given the covariate and other observed auxiliary variables. We propose a class of ...
Linux Journal

Linux Kernel Testing and Debugging

Testing is an integral and important part of any software development cycle, open or closed, and Linux kernel is no exception to that. Developer testing, integration testing, regression, and stress ...