|
|
| 第21行： |
第21行： |
| | *found the cause of cost randomness | | *found the cause of cost randomness |
| | *modified memory weight,ran expriment [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c9/Yanqing-weight%282.0%29.pdf 言情风格][http://cslt.riit.tsinghua.edu.cn/mediawiki/images/e/e4/Biansaishi-weight%282.0%29.pdf 边塞风格] | | *modified memory weight,ran expriment [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c9/Yanqing-weight%282.0%29.pdf 言情风格][http://cslt.riit.tsinghua.edu.cn/mediawiki/images/e/e4/Biansaishi-weight%282.0%29.pdf 边塞风格] |
| − | *read a paper | + | *read a paper[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1e/1610.09889v1.pdf] |
| | *simply expain my code to Miss Feng | | *simply expain my code to Miss Feng |
| | *discussed with liantian about the way of using tensorflow to realize his idea | | *discussed with liantian about the way of using tensorflow to realize his idea |
| Date |
People |
Last Week |
This Week
|
| 2016/12/05
|
Yang Feng |
- rnng+MN: got the result of k-means method and the result is slightly worse;
- fixed the bug;
- analyzed the memory units and changed the calculation of similarity and reran.
- S2S+MN: read the code and discuss with andy about the implementation details;
- checked Wikianswers data and found the answers are usually much longer than the question;
- read 12 QA-related papers in proceedings of ACL16 and EMNLP16 and haven't found proper dataset yet.
- Huilan's work: got a version of better result focusing on syntactical transformation.
|
- rnng+MN: get the result with new similarity calculation.
- S2S+MN: revise the code of tensorflow to make it equivalent to theano's.
- poetry: review the code of Jiyuan
- Huilan's work: continue the work of adding syntactic information.
|
| Jiyuan Zhang |
- restructured code
- found the cause of cost randomness
- modified memory weight,ran expriment 言情风格边塞风格
- read a paper[1]
- simply expain my code to Miss Feng
- discussed with liantian about the way of using tensorflow to realize his idea
|
|
| Andi Zhang |
- deal with zh2en data set and ran them on NTM
- had a small breakthrough about the code
|
- get output of encoder to form memory
- continue on the coding work of seq2seq with MemN2N
|
| Shiyue Zhang |
- found a bug in my code and modified it.
- tried memory with gate and found a big problem of memory.
- reran previous models, the results are not better than baseline. [report]
- reran the original model setting same seed, and got exactly same result.
- published a TRP [2]
|
- try to solve the problem of mem
|
| Guli |
- preparing more data set
- working on add translate module to code
- writing a survey about Chinese-uyghur MT
|
- prepare more data
- prepare for Thesis Report
|
