Bayesian Active Meta-Learning for Black-Box Optimization. (arXiv:2110.09943v2 [cs.LG] CROSS LISTED)

Data-efficient learning algorithms are essential in many practical
applications for which data collection is expensive, e.g., for the optimal
deployment of wireless systems in unknown propagation scenarios. Meta-learning
can address this problem by leveraging data from a set of related learning
tasks, e.g., from similar deployment settings. In practice, one may have
available only unlabeled data sets from the related tasks, requiring a costly
labeling procedure to be carried out before use in meta-learning. For instance,
one may know the …

arxiv bayesian learning meta meta-learning optimization