Xinyi Wang, Hieu Pham, Paul Michel, Antonios Anastasopoulos, Graham Neubig...
TL;DR通过训练适应性评分器的机器学习模型，以及使用可学习的函数对训练数据进行评分，在完成整个训练过程之前就能量化数据的影响，提出了一种名为 Differentiable Data Selection (DDS) 的强化学习方法。该方法在机器翻译和图像分类等任务中提供了显著的计算优势和一致的效果提升
Abstract
To acquire a new skill, humans learn better and faster if a tutor, based on their current knowledge level, informs them of how much attention they should pay to particular content or practice problems. Similarly, a machine learning model could potentially be trained better with a scorer that "adapts" to its current learning state and estimates the importance