Improved Schemes for Episodic Memory-based Lifelong Learning Tianbao Yang

Current deep neural networks can achieve remarkable performance on a single task. However, when the deep neural network is continually trained on a sequence of tasks, it seems to gradually forget the previous learned knowledge. This phenomenon is referred to as catastrophic forgetting and motivates the field called lifelong learning. Recently, episodic memory based approaches such as GEM [1] and A-GEM [2] have shown remarkable performance. In this paper, we provide the first unified view of episodic memory based approaches from an optimization's perspective.