Continual unsupervised representation learning

Continual unsupervised representation learning

Continual learning aims to improve the ability of modern learning systems to deal with non-stationary distributions, typically by attempting to learn a series of tasks sequentially. Prior art in the field has largely considered supervised or reinforcement learning tasks, and often assumes full knowl...

書誌詳細
主要な著者:	Rao, D, Visin, F, Rusu, AA, Teh, YW, Pascanu, R, Hadsell, R
フォーマット:	Conference item
出版事項:	Conference on Neural Information Processing Systems 2019

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