MALSAR: Multi-task learning via Structural Regularization
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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
- Disease Progression Models
- Incomplete Multi-Source Fusion (iMSF)
- Multi-Stage Multi-Source Fusion
- Multi-Task Clustering
- Multi-Task Calibration

If you have any questions regarding MALSAR, please contact Jiayu Zhou at jiayu.zhou@asu.edu.
