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| 第4行： |
第4行： |
| | | rowspan="6"|2016/12/12 | | | rowspan="6"|2016/12/12 |
| | |Yang Feng || | | |Yang Feng || |
| − | *[[s2smn:]] installed tensorflow and ran a toy example (solved problems: version conflict and memory exhausted) | + | *[[s2smn:]] wrote the manual of s2s with tensorflow [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/5/51/Nmt-tensorflow-mannua-yfeng.pdf nmt-manual]] |
| − | *wrote the code of the memory network part | + | *wrote part of the code of mn. |
| − | *[[Huilan:]] prepared for periodical report and system submission. | + | *wrote the manual of Moses [[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 moses-manual]] |
| | + | *[[Huilan:]] fixed the problem of syntax-based translation. |
| | + | *sort out the system and corresponding documents. |
| | || | | || |
| | *[[s2smn:]] finish the manual of nmt tensorflow | | *[[s2smn:]] finish the manual of nmt tensorflow |
| Date |
People |
Last Week |
This Week
|
| 2016/12/12
|
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.
|
- s2smn: finish the manual of nmt tensorflow
- Huilan: system submission
|
| 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
|
|
| Andi Zhang |
- prepared a paraphrase data set that is enumerated from a previous one (ignoring words like "啊呀哈")
- worked on coding bidirectional model under tensorflow, met with NAN problem
|
- ignore NAN problem for now, run it on the same data set used in Theano
|
| Shiyue Zhang |
- finished tsne pictures, and discussed with teachers
- tried experiments with 28-dim mem, but found almost all of them converged to baseline
- returned to 384-dim mem, which is still slightly better than basline.
- found the problem of action mem, one-hot vector is not proper.
- [report]
|
- change one-hot vector to (0, -10000.0, -10000.0...)
- try 1-dim gate
- try max cos
|
| Guli |
- install and run moses
- prepare thesis report
|
- read papers about Transfer learning and solving OOV
|
| 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
|
