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README
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README
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----------------------------------------------------------
-------- 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/CBCL/GURLS/wiki/2-Getting-Started
- Quick intructions on how to run the libraries for a default case can be found here:
https://github.com/CBCL/GURLS/wiki/2-Getting-Started#wiki-Hello_World
- A User manual with several examples can be found here:
https://github.com/CBCL/GURLS/wiki/3-User-Manual#wiki-User_Manual
- A collection of the most useful and common pipelines can be found here:
https://github.com/CBCL/GURLS/wiki/3-User-Manual#wiki-Examples
- The list of all the available methods of the libraries can be found at
https://github.com/CBCL/GURLS/wiki/4-Available-methods
- C++ Code Documentation can be found at: http://cbcl.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