“Tianyi Luo 2015-12-28”版本间的差异
来自cslt Wiki
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===Interested papers === | ===Interested papers === | ||
*Cascading Bandits: Learning to Rank in the Cascade Model(ICML 2015) [[http://zheng-wen.com/Cascading_Bandit_Paper.pdf pdf]] | *Cascading Bandits: Learning to Rank in the Cascade Model(ICML 2015) [[http://zheng-wen.com/Cascading_Bandit_Paper.pdf pdf]] | ||
+ | * Neural Machine Translation by Joint Learning to Align and Translate(ICLR 2015)[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c3/Neural_Machine_Translation_by_Joint_Learning_to_Align_and_Translate.pdf] |
2015年12月28日 (一) 15:30的版本
Plan to do next week
- Enhance the function of couplet generation function.
- To finish the work about make the lab's demo.
- To try new kernel function to model candidate similarity more efficiently.
Work done in this week
- Finish some parts of work about make the lab's demo.
- Finish the work about local-based attention Chinese couplet generation.
开 业 大 吉:
同 行 增 劲 旅:
training corpus:同 行 增 劲 旅 / 商 界 跃 新 军 / ;
test result:
Non-local attention-based:
[ 0.15731922 0.15440576 0.154654 0.13509884 0.13408586 0.13055836 0.13387793] [ 0.15748511 0.15446058 0.15466693 0.13504058 0.1340386 0.13050689 0.13380134] [ 0.15726063 0.15442531 0.15467082 0.13510644 0.13408728 0.13055961 0.1338899 ] [ 0.15715003 0.15439823 0.15466341 0.13514642 0.13413033 0.13059665 0.13391495] [ 0.15717115 0.15440425 0.15468264 0.13513321 0.13412073 0.13058177 0.13390623]
同 行 增 劲 旅 / 春 风 送 四 季 /
Local attention-based:
同 行 增 劲 旅 / 人 情 安 四 春 /
Plan to do next week
- To finish the work about make the lab's demo.
- To finish the work about the poem and couplet generation's SMT method.
- To tackle the problem of attention-based problem.