Maximum Roaming Multi-Task Learning

  title={Maximum Roaming Multi-Task Learning},
  author={Lucas Pascal and Pietro Michiardi and Xavier Bost and Benoit Huet and Maria A. Zuluaga},
Multi-task learning has gained popularity due to the advantages it provides with respect to resource usage and performance. Nonetheless, the joint optimization of parameters with respect to multiple tasks remains an active research topic. Sub-partitioning the parameters between different tasks has proven to be an efficient way to relax the optimization constraints over the shared weights, may the partitions be disjoint or overlapping. However, one drawback of this approach is that it can weaken… 

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