Overcoming Catastrophic Forgetting via Hessian-free Curvature Estimates

ICLR 2020 Anonymous

Learning neural networks with gradient descent over a long sequence of tasks is problematic as their fine-tuning to new tasks overwrites the network weights that are important for previous tasks. This leads to a poor performance on old tasks – a phenomenon framed as catastrophic forgetting... (read more)

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