An accelarated SDCA framework for statistical learning toolbox in R

by Xingguo for R Project for Statistical Computing

Stochastic learning procedure has become an increasingly popular framework, especially for large-scale optimization problems. Our goal in this project is to develop a generic computational system for a large family of linear regression/classification models via the accelerated stochastic dual coordinate ascent method. We describe the design and the implementation plan of our project, and propose a timeline for our development.