论文标题
克服神经网络中灾难性遗忘的自然方法
Natural Way to Overcome the Catastrophic Forgetting in Neural Networks
论文作者
论文摘要
不久前，发现了一种成功克服神经网络中灾难性遗忘的方法。尽管我们知道使用这种方法在将预训练的网络适应特定任务时保持技能的情况，但它尚未获得广泛的分布。在本文中，我们想提出一种基于通过网络中每个连接的总绝对信号来克服灾难性遗忘的替代方法。该方法具有简单的实现，在我们看来，这基本上与动物大脑中发生的过程非常接近，以在随后的学习过程中保留先前学习的技能。我们希望这种方法的易于实施能够为其广泛的应用提供服务。
Not so long ago, a method was discovered that successfully overcomes the catastrophic forgetting in neural networks. Although we know about the cases of using this method to preserve skills when adapting pre-trained networks to particular tasks, it has not obtained widespread distribution yet. In this paper, we would like to propose an alternative method of overcoming catastrophic forgetting based on the total absolute signal passing through each connection in the network. This method has a simple implementation and seems to us essentially close to the processes occurring in the brain of animals to preserve previously learned skills during subsequent learning. We hope that the ease of implementation of this method will serve its wide application.
