GURLS: A Least Squares Library for Supervised Learning
We present GURLS, a least squares, modular, easy-to-extend software library for efficient supervised learning. GURLS is targeted to machine learning practitioners, as well as non- specialists. It offers a number state-of-the-art training strategies for medium and large-scale learning, and routines f...
Main Authors: | Tacchetti, Andrea, Mallapragada, Pavan K., Santoro, Matteo, Rosasco, Lorenzo |
---|---|
Other Authors: | Massachusetts Institute of Technology. Center for Biological & Computational Learning |
Format: | Article |
Language: | en_US |
Published: |
Association for Computing Machinery (ACM)
2013
|
Online Access: | http://hdl.handle.net/1721.1/83259 https://orcid.org/0000-0001-9311-9171 |
Similar Items
-
GURLS: a Toolbox for Regularized Least Squares Learning
by: Tacchetti, Andrea, et al.
Published: (2012) -
Empirical Effective Dimension and Optimal Rates for Regularized Least Squares Algorithm
by: Caponnetto, Andrea, et al.
Published: (2005) -
Fast Rates for Regularized Least-squares Algorithm
by: Caponnetto, Andrea, et al.
Published: (2005) -
Convex Total Least Squares
by: Slavov, Nikolai G, et al.
Published: (2015) -
Models where the least trimmed squares and least median of squares estimators are maximum likelihood
by: Berenguer-Rico, V, et al.
Published: (2019)