Schedule
来自cslt Wiki
目录
- 1 Text Processing Team Schedule
- 1.1 Members
- 1.2 Work Process
- 1.2.1 Reproduce DSSM Baseline (Chao Xing)
- 1.2.2 RNN Poem Processing (Qixin Wang)
- 1.2.3 RNN Question and Answering System (Tianyi Luo)
- 1.2.4 Deep Poem Processing With Image (Ziwei Bai)
- 1.2.5 RNN Music Processing for lyric (Shiyao Li)
- 1.2.6 RNN Key word Poem Processing (Yi Xiong)
- 1.2.7 RNN Piano Processing (Jiyuan Zhang)
- 1.2.8 Recommendation System (Tong Liu)
Text Processing Team Schedule
Members
Former Members
- Rong Liu (刘荣) : 优酷
- Xiaoxi Wang (王晓曦) : 图灵机器人
- Xi Ma (马习) : 清华大学研究生
- DongXu Zhang (张东旭) : --
Current Members
- Tianyi Luo (骆天一)
- Chao Xing (邢超)
- Qixin Wang (王琪鑫)
- Yiqiao Pan (潘一桥)
Work Process
Reproduce DSSM Baseline (Chao Xing)
- 2016-04-13 : Mission : test dssm model, investigate deep neural question answering system.
: Share theano ppt theano : Share tensorflow ppt tensorflow
- 2016-04-12 : Write done dssm tensor flow version.
- 2016-04-11 : Write tensorflow toolkit ppt for intern student.
- 2016-04-10 : Learn tensorflow toolkit.
- 2016-04-09 : Learn tensorflow toolkit.
- 2016-04-08 : Finish theano version.
RNN Poem Processing (Qixin Wang)
RNN Question and Answering System (Tianyi Luo)
Deep Poem Processing With Image (Ziwei Bai)
- 2016-04-10 : web spider to catch a thousand pices of images.
RNN Music Processing for lyric (Shiyao Li)
- 2016-04-09 : web spider to catch a thousand pieces of lyrics.
- 2016-04-10 : extract the keywords in the lyrics
RNN Key word Poem Processing (Yi Xiong)
- 2016-04-09 : Database for N-Gram data storing
- 2016-04-10 : dictionary stored in database , dictionary based segmentation and a simple bigram segmentation
RNN Piano Processing (Jiyuan Zhang)
:2016-4-12:select appropriate midis and run rnnrbm model :2016-4-13:view rnnrbm model‘s code
Recommendation System (Tong Liu)
- 2016-04-09 : 1.read a review:Machine learning:Trends,perspectives, and prospects 2.learn python ,can operate dict and set
- 2016-04-12 : 1.read paper Collaborative Deep Learning for Recommender Systems and take notes.
2. learn the concepts of stacked denoising autoencoder(SDAE).