This is a Matlab implementation of SALSA, a method for high dimensional nonparametric regression using additive approximations. For more details read our paper below.
- Just add the salsa/ subdirectory to your Matlab workspace and you are ready to go.
- Using this library is fairly straightforward. To use with default hyper-parameters just run salsa(Xtr, Ytr) where Xtr,Ytr are the training data and labels.
- To modify hyper-parameters read salsa.m
- We have released 12 of the 16 datasets used in the paper. The other 4 datasets are not public.
- experiments/realDemo.m demonstrates how to use our method on the datasets.
If you use this library in your academic work please cite the following paper: "Additive Approximations in High Dimensional Nonparametric Regression via the SALSA" Kirthevasan Kandasamy, Yaoliang Yu. International Conference on Machine Learning (ICML) 2016.
This software is released under GNU GPL v3(>=) License. Please read LICENSE.txt for more information.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
"Copyright 2015 Kirthevasan Kandasamy"
- For questions/ bug reports please email kandasamy@cs.cmu.edu