Chelsea finn meta learning
Belgian flobert 22
The meta-learner (or the agent) trains the learner (or the model) on a training set that contains a large number of different tasks. In this stage of meta-learning, the model will acquire a prior experience from training and will learn the common features representations of all the tasks.
these meta-learning techniques explicitly train for the ability to quickly adapt so that, at test time, they can learn quickly when faced with new scenarios. To study the problem of learning to learn, we rst develop a clear and formal de nition of the meta-learning problem, its terminology, and desirable properties of meta-learning algo-rithms.