MALSAR (Multi-tAsk Learning via StructurAl Regularization) package

Timelapse: EARTHEREAL from Adonis Pulatus on Vimeo.

I just came across the following new package MALSAR (Multi-tAsk Learning via StructurAl Regularization) by Jiayu Zhou, Jianhui Chen, Jieping Ye. Here is a small description: :

The MALSAR (Multi-tAsk Learning via StructurAl Regularization) package includes the following multi-task learning algorithms:

• Mean-Regularized Multi-Task Learning

• Multi-Task Learning with Joint Feature Selection

• Robust Multi-Task Feature Learning

• Trace-Norm Regularized Multi-Task Learning

• Alternating Structural Optimization

• Incoherent Low-Rank and Sparse Learning

• Robust Low-Rank Multi-Task Learning

• Clustered Multi-Task Learning

• Multi-Task Learning with Graph Structures
  
  Manual
  
  
  The manual for the lastest version can be found here. The manual is also included in the MANUAL folder of the MALSAR package.
  Tutorial
  
  
  We gave a tutorial on multi-task learning at the Twelfth SIAM Internation conference on Data Mining (SDM'12). The tutorial slides can be downloaded here.

The webpage is here. The package will soon be listed in the Big Picture page on Compressive Sensing and in the Matrix Factorization page..




Liked this entry ? subscribe to Nuit Blanche's feed, there's more where that came from. You can also subscribe to Nuit Blanche by Email, explore the Big Picture in Compressive Sensing or the Matrix Factorization Jungle and join the conversations on compressive sensing, advanced matrix factorization and calibration issues on Linkedin.