“Xingchao work”版本间的差异

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=Simple semi-linear autoencoder
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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.
 +
 
And I will compare this work to PCA.
 
And I will compare this work to PCA.
 +
 
We only consider one hidden layer.
 
We only consider one hidden layer.
 +
 
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

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