迁移学习 Transfer Learning 目标:泛化 差别: 迁移学习:学习源参数+迁移到目标任务+微调 元学习:定义元目标+元学习参数 持续学习 Continual Learning (Lifelong Learning/Incremental Learning) 学习一序列的任务 关键:catastrophic forgetting 多任务学习 Multi-task Learning ...
5.7 Continual, Online and Adaptive Learning Continual Learning 指的是能像人一样不断学习。理想情况下,这是在利用前向转移的同时完成的,这样就可以根据过去的经验更好地学习新任务,而不会忘记之前学习过的任务,也不需要存储过去的数据。深度神经网络很难满足这些标准,特别是当它们倾向于忘记在早期任务中看到的信息...
Meta-Learning Representations for Continual Learning: Khurram Javed, Martha White 基于模型的元学习： ...
不过话说回来,本篇论文也是continual learning领域的工作, 只是在meta-learning 层面贡献太小而已,但是因为我没怎么读过continual learning方面文献,真按原文表述来看它进步性还是很大的, 看到用来对比的数据集split MNIST/CIFAR-10/CIFAR-100等 感觉这种规模测试集好像显得有点落后, 而这篇文章又是2021年也就是目前最新...
In this paper, we propose OML, an objective that directly minimizes catastrophic interference by learning representations that accelerate future learning and are robust to forgetting under online updates in continual learning. We show that it is possible to learn naturally sparse representations that are...
In the proposed meta-training scheme, the update predictor is trained to minimize loss on a combination of current and past tasks. We show experimentally that the proposed approach works in the continual learning setting. 展开 关键词: Computer Science - Machine Learning ...
Meta-learning的learn to learn，相比传统的机器学习，进行了一个两层的优化，第一层在trainset上训练，...
为了能够增大内循环轮数,同时又能提升模型更新频率,Large-Scale Meta-Learning with Continual Trajectory Shifting(ICML 2021)提出了一种meta-learning新的优化方法。该方法每一次内循环,都伴随着一次外循环,而不是原来的n次内循环对应一次外循环。该方法的核心如下图左侧更新方法和右侧公式。在右侧的公式中,约等号左...
1、Meta-Learning Representations for Continual Learning Khurram Javed, Martha White Department of Computing Science University of Alberta T6G 1P8 kjavedualberta.ca, whitemualberta.ca Abstract A continual learning agent should be able to build on top of existing knowledge to learn on new data ...
几篇论文实现代码:《Look-Ahead Meta-Learning for Continual Learning》(NeurIPS 2020) GitHub:http://t.cn/A6G35hki [fig6] 《Relation-Aware Collaborative Learning for Unified Aspect-Based Sentiment An...