“Xingchao work”版本间的差异

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Ordered Word Vector
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=Chaos Work=
 
=Chaos Work=
 
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==Binary Word Vector==
== Binary Word Vector ==
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===Reproduce Nested Dropout===
 
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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.
=== SVM based on Binary Vector ===
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====Simple semi-linear autoencoder===
Hinging
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Their first draft work is semi-linear autoencoder, so I will reproduce this work.
15-6-17
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And I will compare this work to PCA.
 
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We only consider one hidden layer.
== Ordered Word Vector ==
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Start at 2015-07-02 20:00
<hr>Ordered Word Vector is a simple dropout method using gaussian distribution sweeping.
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Parameter set N(x / beta) in which beta range from 25 to 100 during training process.
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=== Similarity Test ===
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<hr>This chapter test ordered word vector by semantic similarity. Semantic similarity is most popular task in measure word vector's performance area.
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Using three tasks in semantic task, thank to our ACL reviewers' suggestion.  
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==== Similarity 353 ====
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==== Similarity 999 ====
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==== RG 65 ====
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2015年7月2日 (四) 11:24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