“Tianyi Luo 2016-01-04”版本间的差异
来自cslt Wiki
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=== Work done in this week === | === Work done in this week === | ||
* Finish installing the Moses and conduct the couplet generation experiments with SMT method. [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/d/da/2016-01-04_Tianyi_Luo%27s_couplet_generation.pdf Samples]] | * Finish installing the Moses and conduct the couplet generation experiments with SMT method. [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/d/da/2016-01-04_Tianyi_Luo%27s_couplet_generation.pdf Samples]] | ||
| + | The tutoial about how to install Moses and conduct the training and testing is as following: [[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/7/7f/Moses%E5%AE%89%E8%A3%85%E8%AE%AD%E7%BB%83%E5%85%A8%E8%BF%87%E7%A8%8B.pdf Tutoial]]. | ||
| + | |||
=== Plan to do next week === | === Plan to do next week === | ||
* To finish the work about the SMT method implementation of the poem generation and to extract the SMT features to enhance the function of poem generation and songci generation. | * To finish the work about the SMT method implementation of the poem generation and to extract the SMT features to enhance the function of poem generation and songci generation. | ||
2016年1月4日 (一) 08:37的版本
Plan to do next week
- To finish the work about the SMT method implementation of the poem generation.
- To tackle the problem of attention-based programe.
- To implement the reading comprehension qa system.
- To extract the SMT features to enhance the function of poem generation and songci generation.
Work done in this week
- Finish installing the Moses and conduct the couplet generation experiments with SMT method. [Samples]
The tutoial about how to install Moses and conduct the training and testing is as following: [Tutoial].
Plan to do next week
- To finish the work about the SMT method implementation of the poem generation and to extract the SMT features to enhance the function of poem generation and songci generation.
- To implement the reading comprehension qa system.
Interested papers
- Cascading Bandits: Learning to Rank in the Cascade Model(ICML 2015) [pdf]
