TAWARE A SIMPLE NEURAL ATTENTIVE META-LEARNER
1 minute read ∼ Filed in : A paper noteMeta-leaner is trained on a distribution of similar tasks, in the hopes of generalization to novel but related tasks by learning a high-level strategy that captures the essence of the problem it is asked to solve.
Recent meta-learning approaches are extensively hand-designed, either using architectures specialized to a particular application, or hard-coding algorithmic components that constrain how the meta-learner solves the task.
This paper propose a simple and generic meta-learner architectures.