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cs.LG2022
Efficient Meta-Learning for Continual Learning with Taylor Expansion Approximation
Xiaohan Zou, Tong Lin
Continual learning aims to alleviate catastrophic forgetting when handling consecutive tasks under non-stationary distributions. Gradient-based meta-learning algorithms have shown…
cs.LG2021
Principal Gradient Direction and Confidence Reservoir Sampling for Continual Learning
Zhiyi Chen, Tong Lin
Task-free online continual learning aims to alleviate catastrophic forgetting of the learner on a non-iid data stream. Experience Replay (ER) is a SOTA continual learning method, w…
cs.LG2021
A New Adaptive Gradient Method with Gradient Decomposition
Zhou Shao, Tong Lin
Adaptive gradient methods, especially Adam-type methods (such as Adam, AMSGrad, and AdaBound), have been proposed to speed up the training process with an element-wise scaling term…