April 16, 2020
Despite the success of deep learning, much of its success has existed in settings where the goal is to learn one, single-purpose function from data. However, in many contexts, we hope to optimize neural networks for multiple, distinct tasks (i.e. multi-task learning), and optimize so that what is learned from these tasks is transferable to the acquisition of new tasks (e.g. as in meta-learning).