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Accelerating Deep Learning by Focusing on the Biggest Losers
概
思想很简单, 在训练网络的时候, 每个样本都会产生一个损失L(f(xi),yi)\mathcal{L}(f(x_i),y_i)L(f(xi),yi), 训练的模式往往是批训练, 将一个批次∑iL(f(xi),yi)\sum_i \mathcal{L}(f(x_i),y_i)∑iL(f(xi),yi)所产生的损失的梯度都传回去,
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