• Corpus ID: 220633085

Probabilistic Active Meta-Learning

@article{Kaddour2020ProbabilisticAM,
  title={Probabilistic Active Meta-Learning},
  author={Jean Kaddour and Steind{\'o}r S{\ae}mundsson and Marc Peter Deisenroth},
  journal={ArXiv},
  year={2020},
  volume={abs/2007.08949}
}
Data-efficient learning algorithms are essential in many practical applications where data collection is expensive, e.g., in robotics due to the wear and tear. To address this problem, meta-learning algorithms use prior experience about tasks to learn new, related tasks efficiently. Typically, a set of training tasks is assumed given or randomly chosen. However, this setting does not take into account the sequential nature that naturally arises when training a model from scratch in real-life… 
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