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选择哪种Loss? NCE Loss和Sampled Softmax Loss在召回中都有广泛运用. 从word2vec派生出来的算法,如Airbnb和阿里的EGES召回,都使用的是NCE Loss。准确一点说,是NCE的简化版,NEG Loss。尽管NEG Loss在理论上无法等价原始的超大规模softmax,但是不妨碍学习出高质量的embedding。
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求通俗易懂解释下nce loss? - 知乎
选择哪种Loss? NCE Loss和Sampled Softmax Loss在召回中都有广泛运用. 从word2vec派生出来的算法,如Airbnb和阿里的EGES召回,都使用的是NCE Loss。准确一点说,是NCE的简化版,NEG Loss。尽管NEG Loss在理论上无法等价原始的超大规模softmax,但是不妨碍学习出高质量的embedding。
深度学习中loss值可以为负吗? - 知乎
完全可以是负值,举个例子,用mse作为loss,考虑到目前深度学习一般使用batch梯度下降的方法优化,batch内使用reduce_mean得到标量的梯度,此时在loss上减去一个常量的标量,其数值上等于batch内loss的均值,这样的话得到的loss值一直为0,但是梯度一直存在可以正常优化。
深度学习的loss一般收敛到多少? - 知乎
看题主的意思,应该是想问,如果用训练过程当中的loss值作为衡量深度学习模型性能的指标的话,当这个指标下降到多少时才能说明模型达到了一个较好的性能,也就是将loss作为一个evaluation metrics。 但是就像知乎er们经常说的黑话一样,先问是不是,再问是什么。
深度学习网络收敛之后的loss数值代表什么? - 知乎
loss函数其实可以和预测值与真实值完全不相关。比如我想实现一个图神经网络,用于节点分类的半监督任务,那么我可以简单的采用参数的二范数和随机的任意两节点距离作为loss,此时loss和预测的标签无关。 loss是现实问题抽象成类凸优化问题后,函数的最小值。
有哪些「魔改」loss函数,曾经拯救了你的深度学习模型? - 知乎
回答下正题,loss function还是很容易改的,有次我需要更改我的mini batch的loss 权重,就可以使用pytorch 的reduce功能,得到矩阵以后,直接加权。效果还不错。当然我这个和focal loss并不是一类问题。 感觉还是根据自己的需要去更改自己的loss才最好。
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