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大佬们,请问下:神经网络反向传播时,梯度更新的顺序是从输出往输入方向逐个神经元更新吗?
神经网络前面层的权重Wn的更新依赖靠输出层方向 更新后的权重Wn+1' 吗?
还是说只依赖原来各层的权重W,求完损失后,用损失函数对各层的各个权重W求梯度,不用管其他更新的结果,然后基于旧的W更新W就好。
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