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| 第16行： |
第16行： |
| | |- | | |- |
| | |Jiyuan Zhang || | | |Jiyuan Zhang || |
| − | | + | *ran decoder-memory model, but the effect is not obvious |
| | + | *changed binding way of memory and atten models, can generate different style of poetry |
| | + | *cleanned up our code |
| | + | *wrote a techreport about poemGen |
| | + | *submitted two databases about poemGen and musicGen |
| | || | | || |
| − | | + | *explored a variety of binding ways of memory and atten model |
| | |- | | |- |
| | |Andi Zhang || | | |Andi Zhang || |
| Date |
People |
Last Week |
This Week
|
| 2016/11/21
|
Yang Feng |
rnng+mn
- ran experiments of rnng+mn [report]
- used top-k for memory, under training
sequence-to-sequence + mn
- wrote the proposal
- discussed the details of Andy
Intern interview
Huilan's work
|
|
| Jiyuan Zhang |
- ran decoder-memory model, but the effect is not obvious
- changed binding way of memory and atten models, can generate different style of poetry
- cleanned up our code
- wrote a techreport about poemGen
- submitted two databases about poemGen and musicGen
|
- explored a variety of binding ways of memory and atten model
|
| Andi Zhang |
- prepare new data set for paraphrase, wiped out repetition & most of the noises
- run NMT on fr-en data set and new paraphrase set
- read through source code to find ways to modify it
- helped Guli with running NMT on our server
|
- decide to drop theano or not
- start to work on codes
|
| Shiyue Zhang |
- run rnng on MKL successfully, which can double or triple the speed.
- rerun the original model and get the final result 92.32
- rerun the wrong memory models, still running
- implement the dynamic memory model and get the result 92.54 which is 0.22 better than baseline
- try another structure of memory
|
- try more different models and summary the results
- publish the technical reports
|
| Guli |
|
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