“NLP Status Report 2016-12-05”版本间的差异

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*restructured code
 
*restructured code
 
*found the cause of cost randomness
 
*found the cause of cost randomness
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*modified memory weight,ran expriment [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c9/Yanqing-weight%282.0%29.pdf 言情风格][http://cslt.riit.tsinghua.edu.cn/mediawiki/images/e/e4/Biansaishi-weight%282.0%29.pdf 边塞风格]
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*modified memory weight,ran expriment [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c9/Yanqing-weight%282.0%29.pdf 言情风格][http://cslt.riit.tsinghua.edu.cn/mediawiki/images/e/e4/Biansaishi-weight%282.0%29.pdf 边塞风格][http://cslt.riit.tsinghua.edu.cn/mediawiki/images/e/ec/Atten-model.pdf 无风格]
 
*read a paper[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1e/1610.09889v1.pdf]
 
*read a paper[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1e/1610.09889v1.pdf]
 
*simply expain my code to Miss Feng
 
*simply expain my code to Miss Feng

2016年12月5日 (一) 05:47的版本

Date People Last Week This Week
2016/12/05 Yang Feng
  • rnng+MN: got the result of k-means method and the result is slightly worse;
  • fixed the bug;
  • analyzed the memory units and changed the calculation of similarity and reran.
  • S2S+MN: read the code and discuss with andy about the implementation details;
  • checked Wikianswers data and found the answers are usually much longer than the question;
  • read 12 QA-related papers in proceedings of ACL16 and EMNLP16 and haven't found proper dataset yet.
  • Huilan's work: got a version of better result focusing on syntactical transformation.
  • rnng+MN: get the result with new similarity calculation.
  • S2S+MN: revise the code of tensorflow to make it equivalent to theano's.
  • poetry: review the code of Jiyuan
  • Huilan's work: continue the work of adding syntactic information.
Jiyuan Zhang
  • restructured code
  • found the cause of cost randomness
  • modified memory weight,ran expriment 言情风格边塞风格无风格
  • read a paper[1]
  • simply expain my code to Miss Feng
  • discussed with liantian about the way of using tensorflow to realize his idea
  • improve poem model
Andi Zhang
  • turn to focus on tensorflow codes
  • finish code outputing encoder outputs but have some problems with format
  • finish the part mentioned left
Shiyue Zhang
  • found a bug in my code and modified it.
  • tried memory with gate and found a big problem of memory.
  • reran previous models, the results are not better than baseline. [report]
  • reran the original model setting same seed, and got exactly same result.
  • published a TRP [2]
  • try to solve the problem of mem
Guli
  • preparing more data set
  • working on add translate module to code
  • writing a survey about Chinese-uyghur MT
  • prepare more data
  • prepare for Thesis Report
取自“http://index.cslt.org/mediawiki/index.php?title=NLP_Status_Report_2016-12-05&oldid=24531”