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| 第28行： |
第28行： |
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| | |Shiyue Zhang || | | |Shiyue Zhang || |
| − | * finished tsne pictures, and discussed with teachers | + | * changed the one-hot vector to (0, -inf, -inf...), and retied the experiments. But no improvement showed. |
| − | * tried experiments with 28-dim mem, but found almost all of them converged to baseline | + | * tried 1-dim gate, but converged to baseline |
| − | * returned to 384-dim mem, which is still slightly better than basline. | + | * tried to only train gate, but the best is taking all instance as "right" |
| − | * found the problem of action mem, one-hot vector is not proper. | + | * trying a model similar to attention |
| | * [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/2f/RNNG%2Bmm%E5%AE%9E%E9%AA%8C%E6%8A%A5%E5%91%8A.pdf report]] | | * [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/2f/RNNG%2Bmm%E5%AE%9E%E9%AA%8C%E6%8A%A5%E5%91%8A.pdf report]] |
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| 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.
|
|
| 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
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|
| 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 |
- 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]
|
- 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
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- read papers about Transfer learning and solving OOV
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| 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
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- Use LDA to reduce the dimension of the text in 20news and webkb
|
