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| 第32行： |
第32行： |
| | * tried to only train gate, but the best is taking all instance as "right" | | * tried to only train gate, but the best is taking all instance as "right" |
| | * trying a model similar to attention | | * 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/9/9f/RNNG%2Bmm_experiment_report.pdf report]] |
| | || | | || |
| − | * change one-hot vector to (0, -10000.0, -10000.0...) | + | * try to add true action info when training gate |
| − | * try 1-dim gate | + | * try different scale vectors |
| − | * try max cos | + | * try to change cos to only inner product |
| | |- | | |- |
| | |Guli || | | |Guli || |
| 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
|
|
| 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]
|
- try to add true action info when training gate
- try different scale vectors
- try to change cos to only inner product
|
| 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
|
