cslt Wiki - 用户贡献 [zh-cn]

2016-05

2016-05-27T08:51:17Z

Panyq：/* 总结 */

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

2016-05

2016-05-27T08:48:26Z

Panyq：/* list3 */

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

2016-05

2016-05-27T08:29:27Z

Panyq：/* 总结 */

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

2016-05

2016-05-27T08:29:12Z

Panyq：/* list3 */

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

2016-05

2016-05-27T03:50:08Z

Panyq：/* 总结 */

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

2016-05

2016-05-27T03:45:59Z

Panyq：/* list3 */

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

2016-05

2016-05-27T03:44:20Z

Panyq：/* list3 */

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

2016-05

2016-05-27T03:43:00Z

Panyq：/* list1 */

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

2016-05

2016-05-27T03:42:19Z

Panyq：/* list2 */

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

2016-05

2016-05-27T03:14:50Z

Panyq：以“=list1= {| class="wikitable" |+ 日常花费 ! 时间 !! 事项 !! 支出(元) !!　详细 !! 支付 !!经手人 |- !2016-05-06!! 水果（一） !! 27.5 !! !! 卡 !...”为内容创建页面

'''警告：'''“2016-05”指向这里，但您没有足够的权限来访问它。

Cost

2016-05-27T03:09:01Z

Panyq：

'''警告：'''“Cost”指向这里，但您没有足够的权限来访问它。

Schedule

2016-05-27T02:47:09Z

Panyq：/* Former Members */

=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) : --
* Yiqiao Pan (潘一桥)：继续读研

===Current Members===
* Tianyi Luo (骆天一)
* Chao Xing (邢超)
* Qixin Wang (王琪鑫)
* Aodong Li (李傲冬)
* Aiting Liu (刘艾婷)
* Ziwei Bai (白子薇)

==Work Process==
===Research Task===
====Binary Word Embedding(Aiting)====
[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/97/Binary.pdf binary]

2016-05-25:

1.write my own version of word2vec model

2016-05-23:

1.get tensorflow's word2vec model from(https://github.com/tensorflow/tensorflow/tree/master/tensorflow/models/embedding)
2.learn word2vec_basic model
3.run word2vec.py and word2vec_optimized.py

2016-05-22：

1.find the tf.logical_xor(x,y) method in tensorflow to compute Hamming distance.
2.learn tensorflow's word2vec model

2016-05-21：

1.read Lantian's paper 'Binary Speaker Embedding'
2.try to find a formula in tensorflow to compute Hamming distance.

====Ordered Word Embedding(Aodong)====

: 2016-05-23 :
Basic setup of TensorFlow
Read code of word2vec in TensorFlow
: 2016-05-22 :
Learn about algorithms in word2vec
Read low-freq word papar and learn about 6 strategies

[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/3/39/How_to_deal_with_low_frequency_words.pdf low_freq]

[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/2c/Lowv.pdf order_rep]

====Matrix Factorization(Ziwei)====
[http://papers.nips.cc/paper/5477-neural-word-embedding-as-implicit-matrix-factorization.pdf matrix-factorization]

2016-05-23:
read the code 'map_rawtext_matrix_factorization.py'
2016-05-22：
learn the rest of paper ‘Neural word Embedding as implicit matrix factorization’
2016-05-21：
learn the ‘abstract’ and ‘introduction’ of paper ‘Neural word Embedding as implicit matrix factorization’

===Question answering system===

====Chao Xing====
2016-05-23 :
Find three things to do.
1. Cost function change to maximize QA+ - QA-.
2. Different parameters space in Q space and A space.
3. HRNN separate to two tricky things : use output layer or use hidden layer as decoder's softmax layer's input.
2016-05-22 :
1. Investigate different loss functions in chatting model.
2016-05-21 :
1. Hand out different research task to intern students.
2016-05-20 :
1. Testing denosing rnn generation model.
2016-05-19 :
1. Discover for denosing rnn.
2016-05-18 :
1. Modify model for crawler data.
2016-05-17 :
1. Code & Test HRNN model.
2016-05-16 :
1. Work done for CDSSM model.
2016-05-15 :
1. Test CDSSM model package version.
2016-05-13 :
1. Coding done CDSSM model package version. Wait to test.
2016-05-12 :
1. Begin to package CDSSM model for huilan.
2016-05-11 :
1. Prepare for paper sharing.
2. Finish CDSSM model in chatting process.
3. Start setup model & experiment in dialogue system.
2016-05-10 :
1. Finish test CDSSM model in chatting, find original data has some problem.
2. Read paper:
A Hierarchical Recurrent Encoder-Decoder for Generative Context-Aware Query Suggestion
A Neural Network Approach to Context-Sensitive Generation of Conversational Responses
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
Neural Responding Machine for Short-Text Conversation
2016-05-09 :
1. Test CDSSM model in chatting model.
2. Read paper :
Learning from Real Users Rating Dialogue Success with Neural Networks for Reinforcement Learning in Spoken Dialogue Systems
SimpleDS A Simple Deep Reinforcement Learning Dialogue System
3. Code RNN by myself in tensorflow.
2016-05-08 :
Fix some problem in dialogue system team, and continue read some papers in dialogue system.
2016-05-07 :
Read some papers in dialogue system.
2016-05-06 :
Try to fix RNN-DSSM model in tensorflow. Failure..
2016-05-05 :
Coding for RNN-DSSM in tensorflow. Face an error when running rnn-dssm model in cpu : memory keep increasing.
Tensorflow's version in huilan is 0.7.0 and install by pip, this cause using error in creating gpu graph,
one possible solution is build tensorflow from source code.

====Aiting Liu====

2016-05-25:

1.write my own version of word2vec model

2016-05-23:

1.get tensorflow's word2vec model from(https://github.com/tensorflow/tensorflow/tree/master/tensorflow/models/embedding)
2.learn word2vec_basic model
3.run word2vec.py and word2vec_optimized.py,we need a Chinese evaluation dataset if we want to use it directly

2016-05-22：

1.find the tf.logical_xor(x,y) method in tensorflow to compute Hamming distance.
2.learn tensorflow's word2vec model

2016-05-21：

1.read Lantian's paper 'Binary Speaker Embedding'
2.try to find a formula in tensorflow to compute Hamming distance.

2016-05-18：

Fetch American TV subtitles and process them into a specific format(12.6M)
(1.Sex and the City 2.Gossip Girl 3.Desperate Housewives 4.The IT Crowd 5.Empire 6.2 Broke Girls)

2016-05-16：Process the data collected from the interview site,interview books and American TV subtitles(38.2M+23.2M)

2016-05-11：

Fetch American TV subtitles
(1.Friends 2.Big Bang Theory 3.The descendant of the Sun 4.Modern Family 5.House M.D. 6.Grey's Anatomy)

2016-05-08：Fetch data from 'http://news.ifeng.com/' and 'http://www.xinhuanet.com/'(13.4M)

2016-05-07：Fetch data from 'http://fangtan.china.com.cn/' and interview books (10M)

2016-05-04：Establish the overall framework of our chat robot,and continue to build database

====Ziwei Bai====

2016-05-25:
1、learn DSSM
2、 compelete the first edition of work report
3、construct basic Q&A（name，age，job and so on）
2016-05-23：
write code for searching question in 'zhihu.sogou.com' and searching answer in zhihu
2016-05-21：
learn the second half of paper 'A Neural Conversational Model'
2016-05-18:
1、crawl QA pairs from http://www.chinalife.com.cn/publish/zhuzhan/index.html and http://www.pingan.com/
2、find paper 'A Neural Conversational Model' from google scholar and learn the first half of it.
2016-05-16:
1、find datasets in paper 'Neural Responding Machine for Short-Text Conversation'
2、reconstruct 15 scripts into our expected formula
2016-05-15:
1、find 130 scripts
2、 reconstruct 11 scripts into our expected formula
problem：many files cann't distinguish between dialogue and scenario describes by program.

2016-05-11:
1、read paper“Movie-DiC: a Movie Dialogue Corpus for Research and Development”
2、reconstruct a new film scripts into our expected formula

2016-05-08: convert the pdf we found yesterday into txt，and reconstruct the data into our expected formula

2016-05-07: Finding 9 Drama scripts and 20 film scripts

2016-05-04：Finding and dealing with the data for QA system

===Generation Model (Aodong li)===

: 2016-05-21 : Complete my biweekly report and take over new tasks -- low-frequency words
: 2016-05-20 :
Optimize my code to speed up
Train the models with GPU
However, it does not converge :(
: 2016-05-19 : Code a simple version of keywords-to-sequence model and train the model
: 2016-05-18 : Debug keywords-to-sequence model and train the model
: 2016-05-17 : make technical details clear and code keywords-to-sequence model
: 2016-05-16 : Denoise and segment more lyrics and prepare for keywords to sequence model
: 2016-05-15 : Train some different models and analyze performance: song to song, paragraph to paragraph, etc.
: 2016-05-12 : complete sequence to sequence model's prediction process and the whole standard sequence to sequence lstm-based model v0.0
: 2016-05-11 : complete sequence to sequence model's training process in Theano
: 2016-05-10 : complete sequence to sequence lstm-based model in Theano
: 2016-05-09 : try to code sequence to sequence model
: 2016-05-08 :
denoise and train word vectors of Lijun Deng's lyrics (110+ pieces)
decide on using raw sequence to sequence model
: 2016-05-07 :
study attention-based model
learn some details about the poem generation model
change my focus onto lyrics generation model
: 2016-05-06 : read the paper about poem generation and learn about LSTM
: 2016-05-05 : check in and have an overview of generation model

===jiyuan zhang===
: 2016-05-01~06 :modify input format and run lstmrbm model (16-beat,32-beat,bar)
: 2016-05-09~13:
Modify model parameters and run model ，the result is not ideal yet
According to teacher Wang's opinion, in the generation stage,replace random generation with the maximum probability generation

==Past progress==

[[nlp-progress-2016-05]]

[[nlp-progress-2016-04]]

Schedule

2016-05-27T02:46:47Z

Panyq：/* Current Members */

=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)
* Aodong Li (李傲冬)
* Aiting Liu (刘艾婷)
* Ziwei Bai (白子薇)

==Work Process==
===Research Task===
====Binary Word Embedding(Aiting)====
[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/97/Binary.pdf binary]

2016-05-25:

1.write my own version of word2vec model

2016-05-23:

1.get tensorflow's word2vec model from(https://github.com/tensorflow/tensorflow/tree/master/tensorflow/models/embedding)
2.learn word2vec_basic model
3.run word2vec.py and word2vec_optimized.py

2016-05-22：

1.find the tf.logical_xor(x,y) method in tensorflow to compute Hamming distance.
2.learn tensorflow's word2vec model

2016-05-21：

1.read Lantian's paper 'Binary Speaker Embedding'
2.try to find a formula in tensorflow to compute Hamming distance.

====Ordered Word Embedding(Aodong)====

: 2016-05-23 :
Basic setup of TensorFlow
Read code of word2vec in TensorFlow
: 2016-05-22 :
Learn about algorithms in word2vec
Read low-freq word papar and learn about 6 strategies

[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/3/39/How_to_deal_with_low_frequency_words.pdf low_freq]

[http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/2c/Lowv.pdf order_rep]

====Matrix Factorization(Ziwei)====
[http://papers.nips.cc/paper/5477-neural-word-embedding-as-implicit-matrix-factorization.pdf matrix-factorization]

2016-05-23:
read the code 'map_rawtext_matrix_factorization.py'
2016-05-22：
learn the rest of paper ‘Neural word Embedding as implicit matrix factorization’
2016-05-21：
learn the ‘abstract’ and ‘introduction’ of paper ‘Neural word Embedding as implicit matrix factorization’

===Question answering system===

====Chao Xing====
2016-05-23 :
Find three things to do.
1. Cost function change to maximize QA+ - QA-.
2. Different parameters space in Q space and A space.
3. HRNN separate to two tricky things : use output layer or use hidden layer as decoder's softmax layer's input.
2016-05-22 :
1. Investigate different loss functions in chatting model.
2016-05-21 :
1. Hand out different research task to intern students.
2016-05-20 :
1. Testing denosing rnn generation model.
2016-05-19 :
1. Discover for denosing rnn.
2016-05-18 :
1. Modify model for crawler data.
2016-05-17 :
1. Code & Test HRNN model.
2016-05-16 :
1. Work done for CDSSM model.
2016-05-15 :
1. Test CDSSM model package version.
2016-05-13 :
1. Coding done CDSSM model package version. Wait to test.
2016-05-12 :
1. Begin to package CDSSM model for huilan.
2016-05-11 :
1. Prepare for paper sharing.
2. Finish CDSSM model in chatting process.
3. Start setup model & experiment in dialogue system.
2016-05-10 :
1. Finish test CDSSM model in chatting, find original data has some problem.
2. Read paper:
A Hierarchical Recurrent Encoder-Decoder for Generative Context-Aware Query Suggestion
A Neural Network Approach to Context-Sensitive Generation of Conversational Responses
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models
Neural Responding Machine for Short-Text Conversation
2016-05-09 :
1. Test CDSSM model in chatting model.
2. Read paper :
Learning from Real Users Rating Dialogue Success with Neural Networks for Reinforcement Learning in Spoken Dialogue Systems
SimpleDS A Simple Deep Reinforcement Learning Dialogue System
3. Code RNN by myself in tensorflow.
2016-05-08 :
Fix some problem in dialogue system team, and continue read some papers in dialogue system.
2016-05-07 :
Read some papers in dialogue system.
2016-05-06 :
Try to fix RNN-DSSM model in tensorflow. Failure..
2016-05-05 :
Coding for RNN-DSSM in tensorflow. Face an error when running rnn-dssm model in cpu : memory keep increasing.
Tensorflow's version in huilan is 0.7.0 and install by pip, this cause using error in creating gpu graph,
one possible solution is build tensorflow from source code.

====Aiting Liu====

2016-05-25:

1.write my own version of word2vec model

2016-05-23:

1.get tensorflow's word2vec model from(https://github.com/tensorflow/tensorflow/tree/master/tensorflow/models/embedding)
2.learn word2vec_basic model
3.run word2vec.py and word2vec_optimized.py,we need a Chinese evaluation dataset if we want to use it directly

2016-05-22：

1.find the tf.logical_xor(x,y) method in tensorflow to compute Hamming distance.
2.learn tensorflow's word2vec model

2016-05-21：

1.read Lantian's paper 'Binary Speaker Embedding'
2.try to find a formula in tensorflow to compute Hamming distance.

2016-05-18：

Fetch American TV subtitles and process them into a specific format(12.6M)
(1.Sex and the City 2.Gossip Girl 3.Desperate Housewives 4.The IT Crowd 5.Empire 6.2 Broke Girls)

2016-05-16：Process the data collected from the interview site,interview books and American TV subtitles(38.2M+23.2M)

2016-05-11：

Fetch American TV subtitles
(1.Friends 2.Big Bang Theory 3.The descendant of the Sun 4.Modern Family 5.House M.D. 6.Grey's Anatomy)

2016-05-08：Fetch data from 'http://news.ifeng.com/' and 'http://www.xinhuanet.com/'(13.4M)

2016-05-07：Fetch data from 'http://fangtan.china.com.cn/' and interview books (10M)

2016-05-04：Establish the overall framework of our chat robot,and continue to build database

====Ziwei Bai====

2016-05-25:
1、learn DSSM
2、 compelete the first edition of work report
3、construct basic Q&A（name，age，job and so on）
2016-05-23：
write code for searching question in 'zhihu.sogou.com' and searching answer in zhihu
2016-05-21：
learn the second half of paper 'A Neural Conversational Model'
2016-05-18:
1、crawl QA pairs from http://www.chinalife.com.cn/publish/zhuzhan/index.html and http://www.pingan.com/
2、find paper 'A Neural Conversational Model' from google scholar and learn the first half of it.
2016-05-16:
1、find datasets in paper 'Neural Responding Machine for Short-Text Conversation'
2、reconstruct 15 scripts into our expected formula
2016-05-15:
1、find 130 scripts
2、 reconstruct 11 scripts into our expected formula
problem：many files cann't distinguish between dialogue and scenario describes by program.

2016-05-11:
1、read paper“Movie-DiC: a Movie Dialogue Corpus for Research and Development”
2、reconstruct a new film scripts into our expected formula

2016-05-08: convert the pdf we found yesterday into txt，and reconstruct the data into our expected formula

2016-05-07: Finding 9 Drama scripts and 20 film scripts

2016-05-04：Finding and dealing with the data for QA system

===Generation Model (Aodong li)===

: 2016-05-21 : Complete my biweekly report and take over new tasks -- low-frequency words
: 2016-05-20 :
Optimize my code to speed up
Train the models with GPU
However, it does not converge :(
: 2016-05-19 : Code a simple version of keywords-to-sequence model and train the model
: 2016-05-18 : Debug keywords-to-sequence model and train the model
: 2016-05-17 : make technical details clear and code keywords-to-sequence model
: 2016-05-16 : Denoise and segment more lyrics and prepare for keywords to sequence model
: 2016-05-15 : Train some different models and analyze performance: song to song, paragraph to paragraph, etc.
: 2016-05-12 : complete sequence to sequence model's prediction process and the whole standard sequence to sequence lstm-based model v0.0
: 2016-05-11 : complete sequence to sequence model's training process in Theano
: 2016-05-10 : complete sequence to sequence lstm-based model in Theano
: 2016-05-09 : try to code sequence to sequence model
: 2016-05-08 :
denoise and train word vectors of Lijun Deng's lyrics (110+ pieces)
decide on using raw sequence to sequence model
: 2016-05-07 :
study attention-based model
learn some details about the poem generation model
change my focus onto lyrics generation model
: 2016-05-06 : read the paper about poem generation and learn about LSTM
: 2016-05-05 : check in and have an overview of generation model

===jiyuan zhang===
: 2016-05-01~06 :modify input format and run lstmrbm model (16-beat,32-beat,bar)
: 2016-05-09~13:
Modify model parameters and run model ，the result is not ideal yet
According to teacher Wang's opinion, in the generation stage,replace random generation with the maximum probability generation

==Past progress==

[[nlp-progress-2016-05]]

[[nlp-progress-2016-04]]

Yiqiao Pan 2016-05-16

2016-05-16T02:47:55Z

Panyq：

Weekly Report :

Wrote my thesis.

Upload the audio data.

Prepare for the music generation model.

Yiqiao Pan 2016-05-16

2016-05-16T02:47:46Z

Panyq：

Weekly Report :
Wrote my thesis.

Upload the audio data.

Prepare for the music generation model.

Yiqiao Pan 2016-05-16

2016-05-16T02:47:33Z

Panyq：以“Weekly Report : Wrote my thesis. Upload the audio data. Prepare for the music generation model.”为内容创建页面

Weekly Report :
Wrote my thesis.
Upload the audio data.
Prepare for the music generation model.

2016-05-16

2016-05-16T02:46:16Z

Panyq：

[[Jingyi Lin 2016-05-16]]

[[Qixin Wang 2016-05-16]]

[[Lantian Li 2016-05-16]]

[[Mengyuan Zhao 2016-05-16]]

[[Aodong Li 2016-05-16]]

[[Yang Wang 2016-05-16]]

[[Xuewei Zhang 2016-05-16]]

[[Zhiyuan Tang 2016-05-16]]

[[Chao Xing 2016-05-16]]

[[Xiangyu Zeng 2016-05-16]]

[[Yiqiao Pan 2016-05-16]]

Yiqiao Pan 2016-05-09

2016-05-09T00:55:28Z

Panyq：以“ 1 Wrote the graduation thesis 2 Learned the lenet5 model”为内容创建页面

1 Wrote the graduation thesis

2 Learned the lenet5 model

2016-05-09

2016-05-09T00:52:23Z

Panyq：

[[Mengyuan Zhao 2016-05-09]]

[[Lantian Li 2016-05-09]]

[[Yang Wang 2016-05-09]]

[[Xuewei Zhang 2016-05-09]]

[[Zhiyong Zhang 2016-05-09]]

[[Chao Xing 2016-05-09]]

[[Zhiyuan Tang 2016-05-09]]

[[Aodong Li 2016-05-09]]

[[jiyuan Zhang 2016-05-09]]

[[Yiqiao Pan 2016-05-09]]

ASR work Schedule

2016-05-05T02:40:56Z

Panyq：/* Current Members */

=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)

==Work Process==
===Question & Answering (Aiting Liu)===
: 2016-04-24 : make my biweekly report
: 2016-04-23 : read Fader's paper (2011)
: 2016-04-20 : read Fader's paper (2013)
: 2016-04-15 : learn dssm and sent2vec
: 2016-04-16 : try to figure out how the PARALAX dataset is constructed
: 2016-04-17 : download the PARALAX dataset and try to turn it into what we want it to be

ASR work Schedule

2016-05-05T02:40:47Z

Panyq：/* Work Process */

ASR work Schedule

2016-05-05T02:40:08Z

Panyq：以“=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...”为内容创建页面

=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)
* Aodong Li (李傲冬)
* Ziwei Bai (白子薇)
* Aiting Liu (刘艾婷)

==Work Process==
===Similar questions senetence vector model training with RNN/LSTM and the attention RNN/LSTM chatting model training (Tianyi Luo)===
--------------------2016-04-22
* Speed up process of the test performance about theano version of Generationg the similar questions' vectors based on RNN.
--------------------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. [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/How_to_submit_the_latex_files_including_Chinese_characters_to_arxiv Solution])
* 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.
--------------------2016-04-19
* Optimize theano version of Generationg the similar questions' vectors based on RNN.
--------------------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.

===Reproduce DSSM Baseline (Chao Xing)===
: 2016-04-28 : Given a talk to text team for some recently paper.
Knowledge Base Completion via Search-Based Question Answering : [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b1/Knowledge_Base_Completion_via_Search-Based_Question_Answering_-_Report.pdf pdf]
Open Domain Question Answering via Semantic Enrichment : [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/15/Open_Domain_Question_Answering_via_Semantic_Enrichment_-_Report.pdf pdf]
A Neural Conversational Model : [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/15/A_Neural_Conversational_Model_-_Report.pdf pdf]
And given a tiny results for CNN-DSSM in huilan's weekly report.
: 2016-04-27 : Code Multi-layer CNN, suffered from memory error in GPU in tensorflow.
So I run such test on CPU, should slow.
: 2016-04-26 : Code done tricky & analysis such tricky.
: 2016-04-25 : Find a tricky to improve accuracy given by Tianyi.
: Code for this tricky.
: 2016-04-23 : Set a series of experiment set.
1. Try deep CNN-DSSM, current model just follow proposed model contain one convolution layer, need to be a tuneable parameter.
2. Test whether mixture data effective to current model and deep CDSSM.
3. Code Recurrent CNN-DSSM (new approach.)
: 2016-04-22 : Find a problem : Use labs' gpu machine 970 iteration per time is 1537 second but huilan's server is just 7 second.
Achieve reasonable results when apply max-margin method to CNN-DSSM model.
: 2016-04-21 : True DSSM model doesn't work well, analysis as below:
1. Not exactly reproduce DSSM model, because the original one is English version, I just adapt it to Chinese but after word segmentation.
So the input is tri-gram words not tri-gram letter.
2. Our dataset far from rich, because of we do not use pre-trained word vectors as initial vectors, we can hardly achieve good performance.
: Request
1. As we have rich pre-trained word vectors, maybe CDSSM or RDSSM corrected to our task.
2. Different length of sequences seek to be fixed dimension vectors, just CNN and RNN can do such things, DNN can not do it by using
fix length of word vectors
: Coding done CDSSM. Test for it's performance.
One problem : When you install tensorflow by pip 0.8.0 and you want to use conv2d function by gpu, you need make sure you had already
install your cudnn's version as 4.0 not lastest 5.0.
: 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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 Piano Processing (Jiyuan Zhang)===
:2016-4-12：select appropriate midis and run rnnrbm model
:2016-4-13：view rnnrbm model‘s code
:2016-4-14~15:coding to select 4/4 beat of midis
:2016-4-17~22:run data, failed several times ，then modify code and view rnnrbm model's code
:2016-4-25~29:replace rnnrbm with lstmrbm, then run lstmrbm's model

===Question & Answering (Aiting Liu)===
: 2016-04-24 : make my biweekly report
: 2016-04-23 : read Fader's paper (2011)
: 2016-04-20 : read Fader's paper (2013)
: 2016-04-15 : learn dssm and sent2vec
: 2016-04-16 : try to figure out how the PARALAX dataset is constructed
: 2016-04-17 : download the PARALAX dataset and try to turn it into what we want it to be

===Generation Model (Aodong li)===
: 2016-05-05 : check in

Speech processing

2016-05-05T02:39:47Z

Panyq：

Schedule

2016-05-05T02:37:31Z

Panyq：/* Current Members */

=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)
* Aodong Li (李傲冬)
* Ziwei Bai (白子薇)
* Aiting Liu (刘艾婷)

==Work Process==
===Similar questions senetence vector model training with RNN/LSTM and the attention RNN/LSTM chatting model training (Tianyi Luo)===
--------------------2016-04-22
* Speed up process of the test performance about theano version of Generationg the similar questions' vectors based on RNN.
--------------------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. [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/How_to_submit_the_latex_files_including_Chinese_characters_to_arxiv Solution])
* 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.
--------------------2016-04-19
* Optimize theano version of Generationg the similar questions' vectors based on RNN.
--------------------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.

===Reproduce DSSM Baseline (Chao Xing)===
: 2016-04-28 : Given a talk to text team for some recently paper.
Knowledge Base Completion via Search-Based Question Answering : [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b1/Knowledge_Base_Completion_via_Search-Based_Question_Answering_-_Report.pdf pdf]
Open Domain Question Answering via Semantic Enrichment : [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/15/Open_Domain_Question_Answering_via_Semantic_Enrichment_-_Report.pdf pdf]
A Neural Conversational Model : [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/15/A_Neural_Conversational_Model_-_Report.pdf pdf]
And given a tiny results for CNN-DSSM in huilan's weekly report.
: 2016-04-27 : Code Multi-layer CNN, suffered from memory error in GPU in tensorflow.
So I run such test on CPU, should slow.
: 2016-04-26 : Code done tricky & analysis such tricky.
: 2016-04-25 : Find a tricky to improve accuracy given by Tianyi.
: Code for this tricky.
: 2016-04-23 : Set a series of experiment set.
1. Try deep CNN-DSSM, current model just follow proposed model contain one convolution layer, need to be a tuneable parameter.
2. Test whether mixture data effective to current model and deep CDSSM.
3. Code Recurrent CNN-DSSM (new approach.)
: 2016-04-22 : Find a problem : Use labs' gpu machine 970 iteration per time is 1537 second but huilan's server is just 7 second.
Achieve reasonable results when apply max-margin method to CNN-DSSM model.
: 2016-04-21 : True DSSM model doesn't work well, analysis as below:
1. Not exactly reproduce DSSM model, because the original one is English version, I just adapt it to Chinese but after word segmentation.
So the input is tri-gram words not tri-gram letter.
2. Our dataset far from rich, because of we do not use pre-trained word vectors as initial vectors, we can hardly achieve good performance.
: Request
1. As we have rich pre-trained word vectors, maybe CDSSM or RDSSM corrected to our task.
2. Different length of sequences seek to be fixed dimension vectors, just CNN and RNN can do such things, DNN can not do it by using
fix length of word vectors
: Coding done CDSSM. Test for it's performance.
One problem : When you install tensorflow by pip 0.8.0 and you want to use conv2d function by gpu, you need make sure you had already
install your cudnn's version as 4.0 not lastest 5.0.
: 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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 Piano Processing (Jiyuan Zhang)===
:2016-4-12：select appropriate midis and run rnnrbm model
:2016-4-13：view rnnrbm model‘s code
:2016-4-14~15:coding to select 4/4 beat of midis
:2016-4-17~22:run data, failed several times ，then modify code and view rnnrbm model's code
:2016-4-25~29:replace rnnrbm with lstmrbm, then run lstmrbm's model

===Question & Answering (Aiting Liu)===
: 2016-04-24 : make my biweekly report
: 2016-04-23 : read Fader's paper (2011)
: 2016-04-20 : read Fader's paper (2013)
: 2016-04-15 : learn dssm and sent2vec
: 2016-04-16 : try to figure out how the PARALAX dataset is constructed
: 2016-04-17 : download the PARALAX dataset and try to turn it into what we want it to be

===Generation Model (Aodong li)===
: 2016-05-05 : check in

Schedule

2016-05-05T02:36:06Z

Panyq：/* Work Process */

=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)
* Aodong Li (李傲冬)

==Work Process==
===Similar questions senetence vector model training with RNN/LSTM and the attention RNN/LSTM chatting model training (Tianyi Luo)===
--------------------2016-04-22
* Speed up process of the test performance about theano version of Generationg the similar questions' vectors based on RNN.
--------------------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. [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/How_to_submit_the_latex_files_including_Chinese_characters_to_arxiv Solution])
* 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.
--------------------2016-04-19
* Optimize theano version of Generationg the similar questions' vectors based on RNN.
--------------------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.

===Reproduce DSSM Baseline (Chao Xing)===
: 2016-04-28 : Given a talk to text team for some recently paper.
Knowledge Base Completion via Search-Based Question Answering : [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b1/Knowledge_Base_Completion_via_Search-Based_Question_Answering_-_Report.pdf pdf]
Open Domain Question Answering via Semantic Enrichment : [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/15/Open_Domain_Question_Answering_via_Semantic_Enrichment_-_Report.pdf pdf]
A Neural Conversational Model : [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/15/A_Neural_Conversational_Model_-_Report.pdf pdf]
And given a tiny results for CNN-DSSM in huilan's weekly report.
: 2016-04-27 : Code Multi-layer CNN, suffered from memory error in GPU in tensorflow.
So I run such test on CPU, should slow.
: 2016-04-26 : Code done tricky & analysis such tricky.
: 2016-04-25 : Find a tricky to improve accuracy given by Tianyi.
: Code for this tricky.
: 2016-04-23 : Set a series of experiment set.
1. Try deep CNN-DSSM, current model just follow proposed model contain one convolution layer, need to be a tuneable parameter.
2. Test whether mixture data effective to current model and deep CDSSM.
3. Code Recurrent CNN-DSSM (new approach.)
: 2016-04-22 : Find a problem : Use labs' gpu machine 970 iteration per time is 1537 second but huilan's server is just 7 second.
Achieve reasonable results when apply max-margin method to CNN-DSSM model.
: 2016-04-21 : True DSSM model doesn't work well, analysis as below:
1. Not exactly reproduce DSSM model, because the original one is English version, I just adapt it to Chinese but after word segmentation.
So the input is tri-gram words not tri-gram letter.
2. Our dataset far from rich, because of we do not use pre-trained word vectors as initial vectors, we can hardly achieve good performance.
: Request
1. As we have rich pre-trained word vectors, maybe CDSSM or RDSSM corrected to our task.
2. Different length of sequences seek to be fixed dimension vectors, just CNN and RNN can do such things, DNN can not do it by using
fix length of word vectors
: Coding done CDSSM. Test for it's performance.
One problem : When you install tensorflow by pip 0.8.0 and you want to use conv2d function by gpu, you need make sure you had already
install your cudnn's version as 4.0 not lastest 5.0.
: 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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 Piano Processing (Jiyuan Zhang)===
:2016-4-12：select appropriate midis and run rnnrbm model
:2016-4-13：view rnnrbm model‘s code
:2016-4-14~15:coding to select 4/4 beat of midis
:2016-4-17~22:run data, failed several times ，then modify code and view rnnrbm model's code
:2016-4-25~29:replace rnnrbm with lstmrbm, then run lstmrbm's model

===Question & Answering (Aiting Liu)===
: 2016-04-24 : make my biweekly report
: 2016-04-23 : read Fader's paper (2011)
: 2016-04-20 : read Fader's paper (2013)
: 2016-04-15 : learn dssm and sent2vec
: 2016-04-16 : try to figure out how the PARALAX dataset is constructed
: 2016-04-17 : download the PARALAX dataset and try to turn it into what we want it to be

===Generation Model (Aodong li)===
: 2016-05-05 : check in

Lab Office Supplies

2016-05-05T02:33:13Z

Panyq：/* 电脑及周边 */

'''警告：'''“Lab Office Supplies”指向这里，但您没有足够的权限来访问它。

Lab Office Supplies

2016-05-05T02:23:45Z

Panyq：/* 电脑及周边 */

'''警告：'''“Lab Office Supplies”指向这里，但您没有足够的权限来访问它。

2016-04

2016-05-05T01:59:40Z

Panyq：/* 总结 */

'''警告：'''“2016-04”指向这里，但您没有足够的权限来访问它。

2016-04

2016-05-05T01:52:19Z

Panyq：/* list3 */

'''警告：'''“2016-04”指向这里，但您没有足够的权限来访问它。

2016-04

2016-05-05T01:50:42Z

Panyq：/* list2 */

'''警告：'''“2016-04”指向这里，但您没有足够的权限来访问它。

2016-04

2016-05-05T01:48:20Z

Panyq：/* list1 */

'''警告：'''“2016-04”指向这里，但您没有足够的权限来访问它。

2016-04

2016-05-05T01:47:39Z

Panyq：/* list1 */

'''警告：'''“2016-04”指向这里，但您没有足够的权限来访问它。

2016-04

2016-05-05T01:34:05Z

Panyq：以“=list1= {| class="wikitable" |+ 日常花费 ! 时间 !! 事项 !! 支出(元) !!　详细 !! 支付 !!经手人 |- !2016-03-4!! 米老师机票 !! 1860 !! !! 卡 !!...”为内容创建页面

'''警告：'''“2016-04”指向这里，但您没有足够的权限来访问它。

Cost

2016-05-05T01:33:41Z

Panyq：

'''警告：'''“Cost”指向这里，但您没有足够的权限来访问它。

Schedule

2016-04-22T01:55:00Z

Panyq：/* Work Process */

=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)===
: 2016-04-20 : 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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

Schedule

2016-04-18T02:10:10Z

Panyq：/* RNN Music Processing for lyric (Shiyao Li) */

=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)===
: 2016-04-16 : 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 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)===
: 2016-04-09 : 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)===
: 2016-04-09 : 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)===
: 2016-04-15 :learn dssm and sent2vec
: 2016-04-16 :try to figure out how thePARALAX dataset is constructed
: 2016-04-17 :download the PARALAXdataset and turn it into what we want it to be

Schedule

2016-04-18T02:09:38Z

Panyq：/* 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==
===Reproduce DSSM Baseline (Chao Xing)===
: 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 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)===
: 2016-04-09 : 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

===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
: 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)===
: 2016-04-15 :learn dssm and sent2vec
: 2016-04-16 :try to figure out how thePARALAX dataset is constructed
: 2016-04-17 :download the PARALAXdataset and turn it into what we want it to be

Schedule

2016-04-18T02:07:43Z

Panyq：/* Work Process */

=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)===
: 2016-04-16 : 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 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)===
: 2016-04-09 : 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

===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
: 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)===
: 2016-04-15 :learn dssm and sent2vec
: 2016-04-16 :try to figure out how thePARALAX dataset is constructed

Schedule

2016-04-18T02:04:48Z

Panyq：/* Work Process */

=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)===
: 2016-04-16 : 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 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
: 2016-04-17 :modify the code of CNN and spider

===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
: 2016-04-13 :Read paper Memory Network.
: 2016-04-15 :read the paper Memory Network and start to understand its code
: 2016-04-17 :

===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
: 2016-04-13 : segmentation result analysis
: 2016-04-15 :improve the simple bigram segmentation
: 2016-04-17 :compare the result of bigram segmentation with dictionary segmentation

===RNN Piano Processing (Jiyuan Zhang)===
:2016-4-12：select appropriate midis and run rnnrbm model
:2016-4-13：view rnnrbm model‘s code
: 2016-04-17 :

===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)===
: 2016-04-15 :learn dssm and sent2vec
: 2016-04-17 :try to figure out how thePARALAX dataset is constructed

Yiqiao Pan 2016-04-18

2016-04-18T01:04:46Z

Panyq：以“Weekly Report: Finished plate judge Do some pre-work for music generation”为内容创建页面

Weekly Report:

Finished plate judge

Do some pre-work for music generation

2016-04-18

2016-04-18T01:00:36Z

Panyq：

[[Tianyi Luo 2016-04-18]]

[[Hui Tang 2016-04-18]]

[[Mengyuan Zhao 2016-04-18]]

[[Xiangyu Zeng 2016-04-18]]

[[Zhiyuan Tang 2016-04-18]]

[[Zhiyong Zhang 2016-04-18]]

[[Chao Xing 2016-04-18]]

[[Jiyuan Zhang 2016-04-18]]

[[Xuewei Zhang 2016-04-18]]

[[Qixin Wang 2016-04-18]]

[[Yiqiao Pan 2016-04-18]]

Schedule

2016-04-15T12:50:49Z

Panyq：/* Semantic parsing for single-relation 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==
===Reproduce DSSM Baseline (Chao Xing)===
: 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 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

===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
: 2016-04-13 :Read paper Memory Network.
: 2016-04-15 :read the paper Memory Network and start to understand its code

===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
: 2016-04-13 : segmentation result analysis
: 2016-04-15 :improve the 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).
: 2016-04-15 :

===Question & Answering (Aiting Liu)===
: 2016-04-15 :learn dssm and sent2vec

Schedule

2016-04-15T12:50:19Z

Panyq：/* Recommendation System (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==
===Reproduce DSSM Baseline (Chao Xing)===
: 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 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

===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
: 2016-04-13 :Read paper Memory Network.
: 2016-04-15 :read the paper Memory Network and start to understand its code

===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
: 2016-04-13 : segmentation result analysis
: 2016-04-15 :improve the 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).
: 2016-04-15 :

===Semantic parsing for single-relation Question Answering (Aiting Liu)===
: 2016-04-15 :learn dssm and sent2vec

Schedule

2016-04-15T12:42:39Z

Panyq：/* Work Process */

=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)===
: 2016-04-15 : 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/4/45/2013_-_Learning_Deep_Structured_Semantic_Models_for_Web_Search_using_Clickthrough_Data_-_Report.pdf pdf]
: CNN based DSSM model : A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b7/2014_-_A_Latent_Semantic_Model_with_Convolutional-Pooling_Structure_for_Information_Retrieval_-_Report.pdf pdf]
: Use DSSM model for a new area : Modeling Interestingness with Deep Neural Networks [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/1f/2014_-_Modeling_Interestingness_with_Deep_Neural_Networks_-_Report.pdf pdf]
: Latest approach for LSTM + RNN DSSM model : SEMANTIC MODELLING WITH LONG-SHORT-TERM MEMORY FOR INFORMATION RETRIEVAL [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/2/24/2015_-_SEMANTIC_MODELLING_WITH_LONG-SHORT-TERM_MEMORY_FOR_INFORMATION_RETRIEVAL_-_Report.pdf 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 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

===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
: 2016-04-13 :Read paper Memory Network.
: 2016-04-15 :read the paper Memory Network and start to understand its code

===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
: 2016-04-13 : segmentation result analysis
: 2016-04-15 :improve the 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).
: 2016-04-15 :

===Recommendation System (Aiting Liu)===
: 2016-04-15 :learn dssm and sent2vec

Schedule

2016-04-15T01:17:37Z

Panyq：/* 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)===
: 2016-04-14 : 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 2016-04-13 :1、download theano for python2.7。 2.debug cnn.py

===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
: 2016-04-13 :Read paper Memory Network.

===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
: 2016-04-13 : segmentation result analysis

===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).

Schedule

2016-04-15T01:17:15Z

Panyq：/* RNN Key word Poem Processing (Yi Xiong) */

=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)===
: 2016-04-14 : 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 2016-04-13 :1、download theano for python2.7。 2.debug cnn.py

===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
: 2016-04-13 :Read paper Memory Network.

===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
: 2016-04-13 : segmentation result analysis

===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).

Schedule

2016-04-15T01:16:39Z

Panyq：/* RNN Music Processing for lyric (Shiyao Li) */

=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)===
: 2016-04-14 : 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 2016-04-13 :1、download theano for python2.7。 2.debug cnn.py

===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
: 2016-04-13 :Read paper Memory Network.

===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).

Schedule

2016-04-15T01:16:09Z

Panyq：/* Deep Poem Processing With Image (Ziwei Bai) */

=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)===
: 2016-04-14 : 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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.
: 2016-04-13 :1、download theano for python2.7。 2.debug cnn.py

===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).

Schedule

2016-04-13T08:44:49Z

Panyq：/* 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 [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Theano-RBM.pptx theano]
: Share tensorflow ppt [http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Tensorflow.pptx 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)===

===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).

2016-03

2016-04-12T01:45:08Z

Panyq：/* 总结 */

'''警告：'''“2016-03”指向这里，但您没有足够的权限来访问它。