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Continual learning with tiny episodic memories

Abstract:

In continual learning (CL), an agent learns from a stream of tasks leveraging prior experience to transfer knowledge to future tasks. It is an ideal framework to decrease the amount of supervision in the existing learning algorithms. But for a successful knowledge transfer, the learner needs to remember how to perform previous tasks. One way to endow the learner the ability to perform tasks seen in the past is to store a small memory, dubbed episodic memory, that stores few examples from prev...

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Publication status:
Not published
Peer review status:
Reviewed (other)

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Host title:
Workshop on Multi-Task and Lifelong Reinforcement Learning
Journal:
Workshop on Multi-Task and Lifelong Reinforcement Learning More from this journal
Publication date:
2019-06-15
Acceptance date:
2019-06-10
Keywords:
Subtype:
conference-proceeding
Pubs id:
pubs:1083113
UUID:
uuid:6e7580c4-85c9-4874-a52d-e4184046935c
Local pid:
pubs:1083113
Source identifiers:
1083113
Deposit date:
2020-01-17

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