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Avoiding Catastrophic Forgetting
1Center for Systems Neuroscience, Boston University, 2 Cummington Mall, Boston, MA 02215, USA.
Abstract:
Humans regularly perform new learning without losing memory for previous information, but neural network models suffer from the phenomenon of catastrophic forgetting in which new learning impairs prior function. A recent article presents an algorithm that spares learning at synapses important for previously learned function, reducing catastrophic forgetting.
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