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...
| Auteurs principaux: | , , , , , |
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| Format: | Conference item |
| Publié: |
Conference on Neural Information Processing Systems
2019
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