论文标题
批次级别的经验通过持续学习的评论重播
Batch-level Experience Replay with Review for Continual Learning
论文作者
论文摘要
持续学习是深度学习的一个分支，试图在学习稳定性和可塑性之间取得平衡。 CVPR 2020 Clvision持续学习计算机视觉挑战的持续学习致力于使用Core50数据集评估和推进当前最新的持续学习方法，并具有三种不同的连续学习场景。本文介绍了我们的方法，称为批次经验重播，以评论为挑战。我们的团队在79个参加团队中的所有三种情况下都获得了第一名。我们实施的代码库可在https://github.com/raptormai/cvpr20_clvision_challenge上公开获得
Continual learning is a branch of deep learning that seeks to strike a balance between learning stability and plasticity. The CVPR 2020 CLVision Continual Learning for Computer Vision challenge is dedicated to evaluating and advancing the current state-of-the-art continual learning methods using the CORe50 dataset with three different continual learning scenarios. This paper presents our approach, called Batch-level Experience Replay with Review, to this challenge. Our team achieved the 1'st place in all three scenarios out of 79 participated teams. The codebase of our implementation is publicly available at https://github.com/RaptorMai/CVPR20_CLVision_challenge
