# 稀疏编码自编码表达

 Revision as of 08:18, 8 March 2013 (view source)Kandeng (Talk | contribs) (→Topographic sparse coding[拓扑稀疏编码])← Older edit Revision as of 06:25, 21 March 2013 (view source)Kandeng (Talk | contribs) Newer edit → Line 1: Line 1: [原文] [原文] [原文] [原文] - == Sparse coding[稀疏编码] == + == [稀疏编码] == - + 在稀疏自编码算法中，我们试着学习得到一组权重参数$W$（以及相应的截距$b$），通过这些参数可以使我们得到稀疏特征向量$\sigma(Wx + b)$ ，这些特征向量对于重构输入样本非常有用。 - In the sparse autoencoder, we tried to learn a set of weights $W$ (and associated biases $b$) that would give us sparse features $\sigma(Wx + b)$ useful in reconstructing the input $x$. + - + - [初译] + - + - 稀疏编码 + - + - 在稀疏自编码中，为了用稀疏特征$\sigma(Wx + b)$重新表示输入数据$x$需要学习权重系数$W$（以及对应的偏移量$b$）。 + - + - [一审] + - + - 稀疏编码 + - + - 在稀疏自编码中，为了用稀疏特征$\sigma(Wx + b)$重新表示输入数据$x$需要学习权重系数$W$（以及对应的偏移量$b$）。 + [[File:STL_SparseAE.png | 240px]] [[File:STL_SparseAE.png | 240px]]