Linearized and kernelized sparse multitask learning for predicting cognitive outcomes in alzheimer’s disease

HIGHLIGHTS

• who: Xiaoli Liu et al. from the Computer Science and Engineering, Northeastern University, Shenyang, China have published the article: Linearized and Kernelized Sparse Multitask Learning for Predicting Cognitive Outcomes in Alzheimer’s Disease, in the Journal: Computational and Mathematical Methods in Medicine of 24/01/2018
• what: The authors focus on how the method deals with multitask learning problem in_(7), where G is equal to 𝑝, and each group denotes the corresponding feature shared across the multiple tasks.
• how: For the quantitative performance evaluation the authors employed the metrics of Correlation Coefficient (CC . . .
  

   

  

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