Simultaneous perturbation method for multi-task weight optimization in one-shot meta-learning https://constructor.tech/en-ca/node/293
In this paper we investigate the modification of a standard meta-learning pipeline. The proposed method simultaneously utilizes information from several meta-training tasks in a common loss function.
This problem can be resolved by providing additional information to the model.
