“Tianyi Luo 2015-12-28”版本间的差异

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=== Plan to do next week ===
 
=== Plan to do next week ===
* Enhance the function of couplet generation function.
+
* To finish the work about making the lab's demo.
* To finish the work about make the lab's demo.
+
 
* To try new kernel function to model candidate similarity more efficiently.
 
* To try new kernel function to model candidate similarity more efficiently.
 
=== Work done in this week ===
 
=== Work done in this week ===
* Finish some parts of work about make the lab's demo.
+
* Finish some parts of work about making the lab's demo.
* Finish the work about local-based attention Chinese couplet generation.
+
* Finish the work about local-based attention Chinese couplet generation model.
 
开 业 大 吉:
 
开 业 大 吉:
  
第29行: 第28行:
  
 
=== Plan to do next week ===
 
=== Plan to do next week ===
* To finish the work about make the lab's demo.
+
* To finish the work about making the lab's demo.
* To finish the work about the poem and couplet generation's SMT method.
+
* To finish the work about the SMT method implementation of the poem generation.
* To tackle the problem of attention-based problem.
+
* To tackle the problem of attention-based programe.
 +
* To implement the reading comprehension qa system.
 +
* To extract the SMT features to enhance the function of poem generation and songci generation.
  
 
===Interested papers ===
 
===Interested papers ===
 
*Cascading Bandits: Learning to Rank in the Cascade Model(ICML 2015) [[http://zheng-wen.com/Cascading_Bandit_Paper.pdf pdf]]
 
*Cascading Bandits: Learning to Rank in the Cascade Model(ICML 2015) [[http://zheng-wen.com/Cascading_Bandit_Paper.pdf pdf]]
* Neural Machine Translation by Joint Learning to Align and Translate(ICLR 2015)[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c3/Neural_Machine_Translation_by_Joint_Learning_to_Align_and_Translate.pdf]
+
* Neural Machine Translation by Joint Learning to Align and Translate(ICLR 2015)[[http://xueshu.baidu.com/s?wd=paperuri%3A%283242f94dcbfc892f63c9f51acd8ef8ce%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Farxiv.org%2Fabs%2F1409.0473&ie=utf-8 pdf]]

2015年12月31日 (四) 05:11的最后版本

Plan to do next week

  • To finish the work about making the lab's demo.
  • To try new kernel function to model candidate similarity more efficiently.

Work done in this week

  • Finish some parts of work about making the lab's demo.
  • Finish the work about local-based attention Chinese couplet generation model.

开 业 大 吉:

同 行 增 劲 旅:

training corpus:同 行 增 劲 旅 / 商 界 跃 新 军 /  ;

test result:

Non-local attention-based:

[ 0.15731922 0.15440576 0.154654 0.13509884 0.13408586 0.13055836 0.13387793] [ 0.15748511 0.15446058 0.15466693 0.13504058 0.1340386 0.13050689 0.13380134] [ 0.15726063 0.15442531 0.15467082 0.13510644 0.13408728 0.13055961 0.1338899 ] [ 0.15715003 0.15439823 0.15466341 0.13514642 0.13413033 0.13059665 0.13391495] [ 0.15717115 0.15440425 0.15468264 0.13513321 0.13412073 0.13058177 0.13390623]

同 行 增 劲 旅 / 春 风 送 四 季 /

Local attention-based:

同 行 增 劲 旅 / 人 情 安 四 春 /

Plan to do next week

  • To finish the work about making the lab's demo.
  • To finish the work about the SMT method implementation of the poem generation.
  • To tackle the problem of attention-based programe.
  • To implement the reading comprehension qa system.
  • To extract the SMT features to enhance the function of poem generation and songci generation.

Interested papers

  • Cascading Bandits: Learning to Rank in the Cascade Model(ICML 2015) [pdf]
  • Neural Machine Translation by Joint Learning to Align and Translate(ICLR 2015)[pdf]