Bayesian Multitask Learning with Latent Hierarchies

Hal Daume III

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arXiv · 1408.2032

Bayesian Multitask Learning with Latent Hierarchies

Hal Daume III

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Abstract

We learn multiple hypotheses for related tasks under a latent hierarchical relationship between tasks. We exploit the intuition that for domain adaptation, we wish to share classifier structure, but for multitask learning, we wish to share covariance structure. Our hierarchical model is seen to subsume several previously proposed multitask learning models and performs well on three distinct real-world data sets.

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Hal Daume III. 2014-08-09. Bayesian Multitask Learning with Latent Hierarchies. https://arxiv.org/abs/1408.2032

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