“Schedule”版本间的差异
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==Work Process== | ==Work Process== | ||
+ | ===Similar questions senetence vector training with RNN/LSTM(Tianyi Luo)=== | ||
+ | --------------------2016-04-18 | ||
+ | * Optimize theano version of Generationg the similar questions' vectors based on RNN. | ||
+ | * Finish implementing theano version of LSTM Max margin vector training. | ||
+ | --------------------2016-04-19 | ||
+ | * Optimize theano version of Generationg the similar questions' vectors based on RNN. | ||
+ | --------------------2016-04-20 | ||
+ | * Finish submiting the camera version paper of IJCAI 2016. | ||
+ | * Update the version of Technical Report about Chinese Song Iambics generation. | ||
+ | --------------------2016-04-21 | ||
+ | * Finish helping Teacher Wang to prepare for text group's presentation(Tang poetry and Songci generation and Intelligent QA system) for Tsinghua University's 105 anniversary. | ||
+ | * Submit our IJCAI paper to arxiv. (Solve a big problem about submitting the paper including Chinese chacracters) | ||
+ | * Optimize theano version of Generationg the similar questions' vectors based on RNN. | ||
+ | |||
===Reproduce DSSM Baseline (Chao Xing)=== | ===Reproduce DSSM Baseline (Chao Xing)=== | ||
: 2016-04-20 : Find reproduced DSSM model's bug, fix it. | : 2016-04-20 : Find reproduced DSSM model's bug, fix it. |
2016年4月22日 (五) 03:04的版本
目录
- 1 Text Processing Team Schedule
- 1.1 Members
- 1.2 Work Process
- 1.2.1 Similar questions senetence vector training with RNN/LSTM(Tianyi Luo)
- 1.2.2 Reproduce DSSM Baseline (Chao Xing)
- 1.2.3 Deep Poem Processing With Image (Ziwei Bai)
- 1.2.4 RNN Music Processing for lyric (Shiyao Li)
- 1.2.5 RNN Key word Poem Processing (Yi Xiong)
- 1.2.6 RNN Piano Processing (Jiyuan Zhang)
- 1.2.7 Recommendation System (Tong Liu)
- 1.2.8 Question & Answering (Aiting 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
Similar questions senetence vector training with RNN/LSTM(Tianyi Luo)
2016-04-18
- Optimize theano version of Generationg the similar questions' vectors based on RNN.
- Finish implementing theano version of LSTM Max margin vector training.
2016-04-19
- Optimize theano version of Generationg the similar questions' vectors based on RNN.
2016-04-20
- Finish submiting the camera version paper of IJCAI 2016.
- Update the version of Technical Report about Chinese Song Iambics generation.
2016-04-21
- Finish helping Teacher Wang to prepare for text group's presentation(Tang poetry and Songci generation and Intelligent QA system) for Tsinghua University's 105 anniversary.
- Submit our IJCAI paper to arxiv. (Solve a big problem about submitting the paper including Chinese chacracters)
- Optimize theano version of Generationg the similar questions' vectors based on RNN.
Reproduce DSSM Baseline (Chao Xing)
- 2016-04-20 : Find reproduced DSSM model's bug, fix it.
- 2016-04-19 : Code mixture data model by less memory dependency done. Test it's performance.
- 2016-04-18 : Code mixture data model.
- 2016-04-16 : Code mixture data model, but face to memory error. Dr. Wang help me fix it.
- 2016-04-15 : Share Papers. Investigation a series of DSSM papers for future work. And show our intern students how to do research.
: Original DSSM model : Learning Deep Structured Semantic Models for Web Search using Clickthrough Data pdf : CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval pdf : Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks pdf : Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL pdf
- 2016-04-14 : Test dssm-dnn model, code dssm-cnn model.
Continue investigate deep neural question answering system.
- 2016-04-13 : 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.
Deep Poem Processing With Image (Ziwei Bai)
- 2016-04-20 :combine my program with Qixin Wang's
- 2016-04-10 : web spider to catch a thousand pices of images.
- 2016-04-13 :1、download theano for python2.7。 2.debug cnn.py
- 2016-04-15 :web spider to catch 30 thousands pices of images and store them into a matrix
- 2016-04-16 :modify the code of CNN and spider
- 2016-04-17 :train convouloutional neural network
RNN Music Processing for lyric (Shiyao Li)
- 2016-04-20 : learn LSTM
- 2016-04-09 : web spider to catch a thousand pieces of lyrics.
- 2016-04-10 : extract the keywords in the lyrics
- 2016-04-13 :Read paper Memory Network.
- 2016-04-15 :read the paper Memory Network and start to understand its code
- 2016-04-17 :read paper end to end memory network
RNN Key word Poem Processing (Yi Xiong)
- 2016-04-20 : learn web spider
- 2016-04-09 : Database for N-Gram data storing
- 2016-04-10 : dictionary stored in database , dictionary based segmentation and a simple bigram segmentation
- 2016-04-13 : segmentation result analysis
- 2016-04-15 :improve the simple bigram segmentation
- 2016-04-16 :compare the result of bigram segmentation with dictionary segmentation
- 2016-04-17 :learn python (head first 50%)
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).
- 2016-04-17 :1.allocate PuTTy and Xming 2.learn python, can operate slice and iterator 3.learn release and datasets of a paper: Collaborative Deep Learning for Recommender Systems
Question & Answering (Aiting Liu)
- 2016-04-20 : read Fader's paper ()2013
- 2016-04-15 :learn dssm and sent2vec
- 2016-04-16 :try to figure out how thePARALAX dataset is constructed
- 2016-04-17 :download the PARALAX dataset and turn it into what we want it to be