2021
Theoretical bounds on estimation error for meta-learning
ICLR 2021poster
Machine learning models have traditionally been developed under the assumption that the training and test distributions match exactly. However, recent success in few-shot learning and related problems are encouraging signs that these models can be adapted to more realistic settings where train and t…