Curriculum Learning for Similar Learning Cases

Abstract

In apprications of machine learning, we often need to generate some models for multiple similar cases. In our study, we propose an efficient learning method exploiting the idea of the curriculum learning. Our idea is that we evaluate the effectiveness of a curriculum learning for one problem, then we use the learned curriculum for learning other cases. We apply our proposal method to two small problems, addition and subtraction of integers, using Sequence-to-Sequence model. Our experimental results show that the method works efficiently for some problem settings.