Progressive Neural Networks
A multi-task architecture proposed to mitigate catastrophic forgetting, in which a new column of network layers is added for each new task and connected to features of old columns through lateral connections, with parameters of old columns frozen to avoid forgetting.
Timeline (last 90 days)
The mainstream approaches to addressing catastrophic forgetting fall into three categories: parameter isolation methods (such as Progressive Neural Networks), regularization-based methods (such as the EWC elastic weight consolidation algorithm), and experience replay methods.
The mainstream strategies for addressing catastrophic forgetting fall into three categories: regularization methods (such as EWC), dynamic architecture methods (such as Progressive Neural Networks), and replay methods.
All Facts (2)
The mainstream approaches to addressing catastrophic forgetting fall into three categories: parameter isolation methods (such as Progressive Neural Networks), regularization-based methods (such as the EWC elastic weight consolidation algorithm), and experience replay methods.
50%UnverifiedThe mainstream strategies for addressing catastrophic forgetting fall into three categories: regularization methods (such as EWC), dynamic architecture methods (such as Progressive Neural Networks), and replay methods.
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