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第6行: |
第6行: |
| *[[s2smn:]] read six papers to fix the details of our model; | | *[[s2smn:]] read six papers to fix the details of our model; |
| *wrote the proposal of lexical memory and discussed the details with Teach Wang; | | *wrote the proposal of lexical memory and discussed the details with Teach Wang; |
− | *finished coding and under debugging; | + | *finished coding of only adding attention to the decoder and under debugging; |
| *refine Moses manual [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/92/Moses%E6%93%8D%E4%BD%9C%E6%89%8B%E5%86%8C--%E5%86%AF%E6%B4%8B.pdf manual]] ; | | *refine Moses manual [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/92/Moses%E6%93%8D%E4%BD%9C%E6%89%8B%E5%86%8C--%E5%86%AF%E6%B4%8B.pdf manual]] ; |
| *prepare the dictionary for the memory loading; | | *prepare the dictionary for the memory loading; |
Date |
People |
Last Week |
This Week
|
2016/12/26
|
Yang Feng |
- s2smn: read six papers to fix the details of our model;
- wrote the proposal of lexical memory and discussed the details with Teach Wang;
- finished coding of only adding attention to the decoder and under debugging;
- refine Moses manual [manual] ;
- prepare the dictionary for the memory loading;
- Huilan: documentation
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|
Jiyuan Zhang |
- coded tone_model,but had some trouble
- run global_attention_model that decodes four sentences, fourfivegenerated by local_attention model
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|
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
|
|
Shiyue Zhang |
- tried to add true action info when training gate, which got better results than no true actions, but still not very good.
- tried different scale vectors, and found setting >=-5000 is good
- tried to change cos to only inner product, and inner product is better than cos.
- [report]
- read 3 papers [[1]] [[2]] [[3]]
- trying the joint training, which got a problem of optimization.
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- try the joint training
- read more papers and write a summary
|
Guli |
- read papers about Transfer learning and solving OOV
- conducted comparative test
- writing survey
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- complete the first draft of the survey
|
Peilun Xiao |
- learned tf-idf algorithm
- coded tf-idf alogrithm in python,but found it not worked well
- tried to use small dataset to test the program
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- use sklearn tfidf to test the dataset
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