GURLS: a Toolbox for Regularized Least Squares Learning

GURLS: a Toolbox for Regularized Least Squares Learning

We present GURLS, a toolbox for supervised learning based on the regularized least squares algorithm. The toolbox takes advantage of all the favorable properties of least squares and is tailored to deal in particular with multi-category/multi-label problems. One of the main advantages of GURLS is th...

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Bibliographic Details
Main Authors: Tacchetti, Andrea, Mallapragada, Pavan S., Santoro, Matteo, Rosasco, Lorenzo
Other Authors: Tomaso Poggio
Language:en-US
Published: MIT CSAIL 2012
Subjects:
Matlab
Computational Learning
Regularized Least Squares
Large Scale, Multiclass problems
C++
Online Access:http://hdl.handle.net/1721.1/69034

Internet

http://hdl.handle.net/1721.1/69034

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