Tri-Class Support Vector Machines
Boosting Response Aware Model-Based Collaborative Filtering
Online Learning for Multi-task Feature Selection
Generalized Multiple Kernel Learning
Online Learning for Group Lasso
Localized Support Vector Regression
MEMPM and BMPM
This package is a set of Matlab scripts and demo video that implements the Tri-Class Support Vector Machines.
Download: Ver 0.94c
How to use? You can run the demo in Matlab by typing: demo_3CSVM
Note
In 3CSVM, we suggest you to download Mosek as the QP solver. Otherwise, you may see the following warnings and cannot attain results as we provided.
Warning: Name is nonexistent or not a directory: xxx.
Warning: Large-scale algorithm does not currently solve this problem formulation, using a medium-scale algorithm instead.
Warning: xxx not found in path.
This package is written in C for the paper, Boosting Response AwareModel-Based Collaborative Filtering, IEEE TKDE, 2015.
Download: Codes
This package is a set of Matlab scripts for the paper, Online Learning forMulti-Task Feature Selection.
This package is a set of Matlab scripts for the paper, Generalized Multiple Kernel Learning, IEEE TNNLS, 2013
This package is a set of Matlab scripts for the paper, Online Learning for Group Lasso, ICML’10.
This package is a set of Matlab scripts for the paper, Localized Support Vector Regression, Neurocomputing, 2009.
This package is a set of Matlab scripts for the paper, The Minimum Error Minimax Probability Machine, Journal of Machine Learning Research, 2004.
Download: MEMPM-1.0, BMPM-1.0