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Found 2 papers, 1 papers with code
A simple but strong baseline for online continual learning: Repeated Augmented Rehearsal
Despite its strong empirical performance, rehearsal methods still suffer from a poor approximation of the loss landscape of past data with memory samples.
Closed-loop Control for Online Continual Learning
To address the non-stationarity in the continual learning environment, we employ a Q function with task-specific and task-shared components to support fast adaptation.
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