Tuesday, 6 January 2015

Multi-Task Learning toolkit

Intro: 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
2)
Linkhttp://klcl.pku.edu.cn/member/sunxu/software/MultiTask.zip
Intro: This is a general purpose software for online multi-task learning. The online multi-task learning is mainly based on Conditional Random Fields (CRF) model and Stochastic Gradient Descent (SGD) training.

I am going to deepen this technique for machine translation and domain adaptation.

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