“Xingchao work”版本间的差异
来自cslt Wiki
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====Simple semi-linear autoencoder=== | ====Simple semi-linear autoencoder=== | ||
Their first draft work is semi-linear autoencoder, so I will reproduce this work. | Their first draft work is semi-linear autoencoder, so I will reproduce this work. | ||
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And I will compare this work to PCA. | And I will compare this work to PCA. | ||
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We only consider one hidden layer. | We only consider one hidden layer. | ||
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Start at 2015-07-02 20:00 | Start at 2015-07-02 20:00 | ||
2015年7月2日 (四) 11:25的版本
目录
Chaos Work
Binary Word Vector
Reproduce Nested Dropout
Nested dropout method proposed by Rippel et. in their paper "Learning Ordered Representations with Nested Dropout", they proposed a dropout method which could learning ordered information in different dimensions.
=Simple semi-linear autoencoder
Their first draft work is semi-linear autoencoder, so I will reproduce this work.
And I will compare this work to PCA.
We only consider one hidden layer.
Start at 2015-07-02 20:00
