Multilinear Multitask Learning

  title={Multilinear Multitask Learning},
  author={Bernardino Romera-Paredes and M. S. Hane Aung and Nadia Bianchi-Berthouze and Massimiliano Pontil},
Many real world datasets occur or can be arranged into multi-modal structures. With such datasets, the tasks to be learnt can be referenced by multiple indices. Current multitask learning frameworks are not designed to account for the preservation of this information. We propose the use of multilinear algebra as a natural way to model such a set of related tasks. We present two learning methods; one is an adapted convex relaxation method used in the context of tensor completion. The second… CONTINUE READING
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