Difference between revisions of "NLP Status Report 2016-12-19"

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|Andi Zhang ||
 
|Andi Zhang ||
*prepared a paraphrase data set that is enumerated from a previous one (ignoring words like "啊呀哈")
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*tried to modify the wrong softmax, but abandoned at last
*worked on coding bidirectional model under tensorflow, met with NAN problem
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*added bleu scoring part
 
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*ignore NAN problem for now, run it on the same data set used in Theano
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*extract encoder outputs
 
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|Shiyue Zhang ||  
 
|Shiyue Zhang ||  

Revision as of 05:27, 19 December 2016

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
  • attempted to use memory model to improve the atten model of bad effect
  • With the vernacular as the input,generated poem by local atten model[1]
  • Modified working mechanism of memory model(top1 to average)
  • help andi
  • improve poem model
Andi Zhang
  • tried to modify the wrong softmax, but abandoned at last
  • added bleu scoring part
  • 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
  • Read a paper about document classification wiht GMM distributions of word vecotrs and try to code it in python
  • Use LDA to reduce the dimension of the text in r52、r8 and contrast the performance of classification
  • Use LDA to reduce the dimension of the text in 20news and webkb