• Corpus ID: 219179403

Meta Learning as Bayes Risk Minimization

@article{Maeda2020MetaLA,
  title={Meta Learning as Bayes Risk Minimization},
  author={Shin-ichi Maeda and Toshiki Nakanishi and Masanori Koyama},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.01488}
}
Meta-Learning is a family of methods that use a set of interrelated tasks to learn a model that can quickly learn a new query task from a possibly small contextual dataset. In this study, we use a probabilistic framework to formalize what it means for two tasks to be related and reframe the meta-learning problem into the problem of Bayesian risk minimization (BRM). In our formulation, the BRM optimal solution is given by the predictive distribution computed from the posterior distribution of… 

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