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| 第5行： |
第5行： |
| | |Yang Feng || | | |Yang Feng || |
| | * Got the sampled 100w good data and ran Moses (BLEU: 30.6) | | * Got the sampled 100w good data and ran Moses (BLEU: 30.6) |
| − | * Reimplemented the idea of ACL (added some optimization to the previous code) and check the performance in the following gradual steps: 1. use s\_i-1 as memory query; 2. use s\_i-1+c\_i as memory query; 3. use y as the memory states for attention; 4. use y + smt_attentions * h as memory states for attention. | + | * Reimplemented the idea of ACL (added some optimization to the previous code) and check the performance in the following gradual steps: 1. use s_i-1 as memory query; 2. use s_i-1+c_i as memory query; 3. use y as the memory states for attention; 4. use y + smt_attentions * h as memory states for attention. |
| | * ran experiments for the above steps but the loss was inf. I am looking for reasons. | | * ran experiments for the above steps but the loss was inf. I am looking for reasons. |
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| Date |
People |
Last Week |
This Week
|
| 2017/4/5
|
Yang Feng |
- Got the sampled 100w good data and ran Moses (BLEU: 30.6)
- Reimplemented the idea of ACL (added some optimization to the previous code) and check the performance in the following gradual steps: 1. use s_i-1 as memory query; 2. use s_i-1+c_i as memory query; 3. use y as the memory states for attention; 4. use y + smt_attentions * h as memory states for attention.
- ran experiments for the above steps but the loss was inf. I am looking for reasons.
|
- do experiments and write the paper
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| Jiyuan Zhang |
- I did keyword expansion on the qx's model
- fixed some bugs
- read two papers
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- improve the effect of the qx's model
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| Andi Zhang |
- revise the original oov model so that it can automatically detect oov words and translate them
- deal with the situation that source word is oov but target word is not oov first
- it didn't predict right
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- make the model work as what we wanted
- deal with the situation that source word is oov and target word is also oov, then other situations
|
| Shiyue Zhang |
- got a reasonable baseline on big zhen data
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- implement mem model on this baseline, and test on big data
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| Peilun Xiao |
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