This project provides a parallel implementation of the Cholesky factorization algorithm designed to run efficiently on a GPU using CUDA. Cholesky factorization factors a symmetric positive definite ...

Block Cholesky Decomposition consists of two small applications (factor.cpp and solve.cpp). The factor step generates a block tridiagonal matrix, then performs a block Cholesky factorization using ...

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 the kernel matrix inverse (Cholesky ...

Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...

The column elimination tree data-structure provides a very compressed representation of fill-in and the task graph for sparse factorization algorithms. It is often presented heavily with some graph ...