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Zhou Lin

1 accepted papers

2019

Overcoming Catastrophic Forgetting for Continual Learning via Model Adaptation

ICLR 2019poster

Learning multiple tasks sequentially is important for the development of AI and lifelong learning systems. However, standard neural network architectures suffer from catastrophic forgetting which makes it difficult for them to learn a sequence of tasks. Several continual learning methods have been p…

Cited by 211SourcePDFScholar