Abstract Catastrophic forgetting in neural networks is a common problem. in which neural networks lose information from previous tasks after training on new tasks. Although adopting a regularization method that preferentially retains the parameters important to the previous task to avoid catastrophic forgetting has a positive effect; existing regularization methods cause the gradient ... https://chefesquipmenters.shop/product-category/cutting-board-sets/
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