可视化自编码器训练结果

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可视化自编码器训练结果
可视化自编码器训练结果
【原文】:
【原文】:
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Having trained a (sparse) autoencoder, we would now like to visualize the function learned by the algorithm, to try to understand what it has learned. Consider the case of training an autoencoder on [[File:http://deeplearning.stanford.edu/wiki/images/math/0/4/a/04aaf6cd0499a40a7c222ffdb85b55bb.png]] images, so that . Each hidden unit   computes a function of the input:
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Having trained a (sparse) autoencoder, we would now like to visualize the function
 +
learned by the algorithm, to try to understand what it has learned.
 +
Consider the case of training an autoencoder on <math>\textstyle 10 \times 10</math> images, so that <math>\textstyle n = 100</math>.
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Each hidden unit <math>\textstyle i</math> computes a function of the input:
【初译】:
【初译】:
得到了训练好的(稀疏)自编码器,我们就可以将通过算法习得的函数进行可视化,以便于了解学习的结果。我们以使用10×10的图像来训练自编码器为例,此时n=100。针对每个隐藏单元i,将输入值代入以下方程:
得到了训练好的(稀疏)自编码器,我们就可以将通过算法习得的函数进行可视化,以便于了解学习的结果。我们以使用10×10的图像来训练自编码器为例,此时n=100。针对每个隐藏单元i,将输入值代入以下方程:

Revision as of 10:44, 7 March 2013

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