“NLP Status Report 2016-12-19”版本间的差异

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（某位用户的一个中间修订版本未显示）
第20行： 第20行：
 
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|Andi Zhang ||
 
|Andi Zhang ||
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*tried to modify the wrong softmax, but abandoned at last
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*coded to output encoder outputs and correspoding source & target sentences(ids in dictionaries)
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*added bleu scoring part
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*coded a script for bleu scoring, which tests the five checkpoints auto created by training process and save the one with best performance
 
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*extract encoder outputs
 
*extract encoder outputs
第44行： 第44行：
 
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|Peilun Xiao ||
 
|Peilun Xiao ||
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*Use LDA to generate 10-500 dimension document vector in the rest datasets
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*use LDA to generate 10-500 dimension document vector in the rest datasets
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*Write a python code about a new algorithm about tf-idf
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*write a python code about a new algorithm about tf-idf
 
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*Debug the code
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*debug the code
 
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2016年12月26日 (一) 00:58的最后版本

Date People Last Week This Week
2016/12/19 Yang Feng
  • s2smn: wrote the manual of s2s with tensorflow [nmt-manual]
  • wrote part of the code of mn.
  • wrote the manual of Moses [moses-manual]
  • Huilan: fixed the problem of syntax-based translation.
  • sort out the system and corresponding documents.
Jiyuan Zhang
  • coded tone_model,but had some trouble
  • run global_attention_model that decodes four sentences, fourfivegenerated by local_attention model
  • improve poem model
Andi Zhang
  • coded to output encoder outputs and correspoding source & target sentences(ids in dictionaries)
  • coded a script for bleu scoring, which tests the five checkpoints auto created by training process and save the one with best performance
  • extract encoder outputs
Shiyue Zhang
  • changed the one-hot vector to (0, -inf, -inf...), and retied the experiments. But no improvement showed.
  • tried 1-dim gate, but converged to baseline
  • tried to only train gate, but the best is taking all instance as "right"
  • trying a model similar to attention
  • [report]
  • try to add true action info when training gate
  • try different scale vectors
  • try to change cos to only inner product
Guli
  • read papers about Transfer learning and solving OOV
  • conducted comparative test
  • writing survey
  • complete the first draft of the survey
Peilun Xiao
  • use LDA to generate 10-500 dimension document vector in the rest datasets
  • write a python code about a new algorithm about tf-idf
  • debug the code
取自“http://index.cslt.org/mediawiki/index.php?title=NLP_Status_Report_2016-12-19&oldid=25027”