Batch-level Experience Replay with Review for Continual Learning

Current CL methods can be taxonomized into three major categories: regularization-based, parameter isolation, Continual learning is a branch of deep learning that and memory-based methods [14]. Some regularizationbased seeks to strike a balance between learning stability and methods encode the knowledge from past tasks into plasticity. The CVPR 2020 CLVision Continual Learning a prior and utilize the prior to either regularize the update for Computer Vision challenge is dedicated to evaluating of parameters that were important to past tasks [8, 18, 13] and advancing the current state-of-the-art continual while others leverage knowledge distillation from the model learning methods using the CORe50 dataset with trained on previous tasks to the model being trained on three different continual learning scenarios.