“NLP Status Report 2016-09-26”版本间的差异

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第6行: 第6行:
 
*prepared the phrasal check of Huilan
 
*prepared the phrasal check of Huilan
 
*prepared and discussed the main idea of next work
 
*prepared and discussed the main idea of next work
*learned Lua and Cuda and read the code of MemNN
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*learned Lua and Torch and read the code of MemNN
 
*read the code of rnng
 
*read the code of rnng
 
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*run the experiments of MN grammar
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*modify the code to MN grammar and run the experiments
 
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|Jiyuan Zhang ||
 
|Jiyuan Zhang ||
*completed the illustration of my part of book [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/46/Deep_learning-zhang_jiyuan.pdf here]]
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*ran two versions of the code that qixin gave me,the last version of the result is good
*read two papers about generation task [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c7/Automatic_poetry_composition_through_recurrent_neural_networks_with_iterative_polishing_schema.pdf here]] [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/e/ed/Chinese_couplet_generation_with_neural_network_structures.pdf here]]
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*perfected my poem's code
*checked  qixi’ newly code
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*Results for all versions of the code[[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/7/72/Theme.pdf here]]
 
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*generate the same level poem compared to qx’s
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*perfect my code  according to up-to-date version of qixin's code
 
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|Aodong Li ||  
 
|Aodong Li ||  
第24行: 第24行:
 
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|Andi Zhang ||
 
|Andi Zhang ||
*read several papers about memory network & IE
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*read the sorce code of MemN2N
*tried to set the env for source code
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*installed torch
*ran several times of source code on my laptop, didn't get as good results as in the paper but is close
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*work on rnng
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*try to fit the params of rnng into memn2n
*share a paper about IE
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|Shiyao Li ||
 
|Shiyao Li ||
*prepare for the paper sharing
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*review the chapter 8 of the book written by Maoning Wang
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*learn how to use cvs and how to write books using Latex
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*complete the chapter 8-nonparametric model
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*prepare to write Genetic Algorithm
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|Shiyue Zhang ||  
 
|Shiyue Zhang ||  
*ran rnng code successfully
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*ran rnng code successfully: the result of discriminative model is a bit better than original paper; the generative model has not fully trained, so the performance is worse.
 
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*get generative model f1 score
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*get the states of each timestep
 
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2016年9月26日 (一) 06:18的最后版本

Date People Last Week This Week
2016/09/26 Yang Feng
  • prepared the phrasal check of Huilan
  • prepared and discussed the main idea of next work
  • learned Lua and Torch and read the code of MemNN
  • read the code of rnng
  • modify the code to MN grammar and run the experiments
Jiyuan Zhang
  • ran two versions of the code that qixin gave me,the last version of the result is good
  • perfected my poem's code
  • Results for all versions of the code[here]
  • perfect my code according to up-to-date version of qixin's code
Aodong Li
Andi Zhang
  • read the sorce code of MemN2N
  • installed torch
  • try to fit the params of rnng into memn2n
Shiyao Li
Shiyue Zhang
  • ran rnng code successfully: the result of discriminative model is a bit better than original paper; the generative model has not fully trained, so the performance is worse.
  • get generative model f1 score
  • get the states of each timestep