Multitask Learning via Mixture of Linear Subspaces

@inproceedings{Rai2010MultitaskLV,
  title={Multitask Learning via Mixture of Linear Subspaces},
  author={Piyush Rai and Hal Daum{\'e}},
  year={2010}
}
We propose a probabilistic generative model for multitask learning that exploits the cluster structure of the task parameters, and additionally imposes a low-rank constraint on the set of task parameters within each cluster. This leads to a sharing of statistical strengths of multiple tasks at two levels: (1) via cluster assumption, and (2) via a subspace… CONTINUE READING