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

Kernel Density Estimation (KDE): A nonparametric method to estimate the probability density function of a random variable by averaging over locally weighted contributions of each data point.

The specific type of kernel regression presented in this article is Nadaraya-Watson kernel regression using a radial basis function kernel. The term "kernel regression" by itself is ambiguous because ...

Zhongda Tian, Shujiang Li, Yanhong Wang, Xiangdong Wang, Wind power prediction method based on hybrid kernel function support vector machine, Wind Engineering, Vol. 42, No. 3 (June 2018), pp. 252-264 ...

The fuzzy kernel function clustering algorithm based on semi-supervised learning is used to extract the features of ocean remote sensing and classify marine remote sensing images.

The core idea of quantum kernel learning lies in using quantum computers to compute specific kernel functions that classical computers cannot efficiently calculate due to computational complexity.

The OpenCL kernel-level functions in the Noise sample code associated with this paper takes an approach more suitable for the OpenCL approach to dividing work into parallel operations.

The integer overflow flaw (CVE-2018-14634)exists in a critical Linux kernel function for memory management and allows attackers with unprivileged local access to a system to escalate their privileges.