---------------------------------------------------------- -------- Grand Unified Regularized Least Squares --------- ---------------------------------------------------------- Table of Contents ================= - Introduction - Documentation Introduction ============ The GRAND UNIFIED REGULARIZED LEAST SQUARES software library comprises the following packages. -GURLS, a MATLAB software library for regression and (multiclass) classification based on the Regularized Least Squares (RLS) loss function. Datasets that fit into your computer's memory should be handled with this package. -bGURLS (b is for big), a MATLAB software library that allows to use RLS on very large matrices by means of memory-mapped storage and a simple distributed task manager. -GURLS++, a C++ standalone implementation of GURLS, with additional simple API's for specific learning pipelines -bGURLS++, a C++ standalone implementation of bGURLS. Documentation ============= - Webpage the GURLS webpage can be found at: http://lcsl.mit.edu/gurls.html - Reference paper Tacchetti, Mallapragada, Santoro and Rosasco, Gurls: a least squares-based library for state of the art supervised learning accepted for publication on JMLR - Installation instructions can be found here: https://github.com/LCSL/GURLS/wiki/2-Getting-Started - Quick intructions on how to run the libraries for a default case can be found here: https://github.com/LCSL/GURLS/wiki/2-Getting-Started#wiki-Hello_World - A User manual with several examples can be found here: https://github.com/LCSL/GURLS/wiki/3-User-Manual#wiki-User_Manual - A collection of the most useful and common pipelines can be found here: https://github.com/LCSL/GURLS/wiki/3-User-Manual#wiki-Examples - The list of all the available methods of the libraries can be found at https://github.com/LCSL/GURLS/wiki/4-Available-methods - C++ Code Documentation can be found at: http://lcsl.github.io/GURLS/ - Further Documentation * Have a look at the README files of each individual package. * In gurls-manual.pdf you can find both the installation instructions and user manual, together with the Matlab and C++ Developer's Guide. GURLS is designed for easy expansion. Give it a try! * In recursiveRLS-tutorial.pdf you can find a simple Tutorial for the Recursive RLS API * The description of the available methods, demos and data for each package can be found at https://github.com/CBCL/GURLS/wiki/4-Code-Description