这也就是在分类问题中常用cross entropy 而不是 MSE的原因了。
The Cross-Entropy Loss Function for the Softmax Function 作者:凯鲁嘎吉 - 博客园 http://www.cnblogs.com/kailugaji/ 本文介绍含有softmax函数的交叉熵损失函数的求导过程,并介绍一种交叉熵损失的
Softmax loss和交叉熵损失（Cross-Entropy Loss）是相关但不完全相同的概念。
The cross-entropy method. In James J. Cochran, Louis A. Cox, Pinar Keskinocak, Jeffrey P. Kharoufeh, and J. Cole Smith, editors, Wiley Encyclopedia of Operations Research and Management Science. Wiley & Sons, New York, 2010.D. P. Kroese. The cross-entropy method. In Wiley Encyclopedia...
分类交叉熵损失衡量预测概率与实际标签间的差异，专用于多类分类任务。在多类分类问题中，每个样本只属于一个类。交叉熵接受两个离散概率分布作为输入，输出表示两个分布相似度的数值。该损失函数在多类分类任务中，利用softmax层生成的概率与独热编码标签对比，通过最小化损失促使预测概率接近实际标签。此...
In short, cross-entropy is exactly the same as the negative log likelihood (these were two concepts that were originally developed independently in the field of computer science and statistics, and they are motivated differently, but it turns out that they compute excactly the same in our classi...
The cross-entropy (CE) method is one of the most significant developments in stochastic optimization and simulation in recent years. This book explains in detail how and why the CE method works. The CE method involves an iterative procedure where each iteration can be broken down into two phase...
The cross-entropy (CE) method is an adaptive importance sampling procedure that has been successfully applied to a diverse range of complicated simulation problems. However, recent research has shown that in some high-dimensional settings, the likelihood ratio degeneracy problem becomes severe and the...
The cross-entropy (CE) method is a new generic approach to combinatorial and multi-extremal optimization and rare event simulation. The purpose of this tut
CrossEntropyLoss 据pytorch的官方文档,torch.nn.functional里的cross_entropy是基于log_softmax和nll_loss实现的。 没关系,通过最简单的torch原函数复现,可以较深理解当中的原理。 importtorchdefmy_cross_entropy(input, target, reduction="mean"):#input.shape: torch.size([-1, class])#target.shape: torch....