cslt Wiki - 用户贡献 [zh-cn]

Finance-weekly-reading

2018-03-31T09:31:41Z

Wangcx：

{|class='wikitable'
!Time !! Title !! Leader !! Paper
|-
|2015-08-03 ||Detect & Describe: Deep learning of bank stress in the news || Dong Wang || Samuel Ronnqvist, Peter Sarlin, arxiv 2015.07.25 [[http://arxiv.org/pdf/1507.07870.pdf pdf]]
|-
|2015-08-05 ||Analysis of Hidden Markov Models and Support vector machines in financial applications|| Rong Liu || Satish Rao Jerry Hong 2010[http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-63.pdf pdf]
|-
|2015-08-10 ||NEURAL NETWORKS APPLIED TO STOCK MARKET FORECASTING: AN EMPIRICAL ANALYSIS|| Yang Yu || Leandro Maciel, Rosangela Ballini 2010 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/7/76/NEURAL_NETWORKS_APPLIED_TO_STOCK_MARKET_FORECASTING_AN_EMPIRICAL_ANALYSIS.pdf pdf]
|-
|2015-08-12 ||A Decision Tree-Rough Set Hybrid System for Stock Market Trend Prediction|| Rong Liu || 2010 [http://www.ijcaonline.org/volume6/number9/pxc3871449.pdf pdf]
|-
|2015-08-12 ||A Comparision of Three Network Portfolio Selection Methods || Dong Wang || 2015 [http://arxiv.org/pdf/1512.01905.pdf pdf]
|-
|2016-06-12 ||Online Portfolio Selection: A Survey || Maoning Wang|| January 2014 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/9b/A35-li.pdf pdf]
|-
|2016-06-12 ||SEQUENTIALMONTECARLOSAMPLINGFORCORRELATEDLATENTLONG-MEMORY TIME-SERIE || Maoning Wang|| ICASSP 2016 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b4/0006580.pdf pdf]
|-
|2016-06-17 ||PAMR: Passive Aggressive Mean Reversion Strategy for Portfolio Selection|| Author: LiBin|| Machine Learning May 2012, Volume 87, Issue 2, pp 221-258 [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.421.579&rep=rep1&type=pdf pdf]
|-
|2016-06-17 ||随机微分方程简介|| Author: 陈堰平|| ppt 2008年12月14日 [http://cos.name/wp-content/uploads/2008/12/stochastic-differential-equation-with-r.pdf pdf]
|-
|2016-06-24 ||Where are contrarian profits due to stock market overreaction|| Caixia Wang|| [http://www.finance.martinsewell.com/stylized-facts/dependence/LoMacKinlay1990.pdf pdf]
|-
|2016-07-16 ||Sentiment Analysis in Finance Market Forcast||Dong Wang || [http://wangd.cslt.org/talks/pdf/SentimentAnalysisinFinanceMarketForcast.pptx slides]
|-
|2016-08-20 ||经管量化分析研讨会|| -||[[媒体文件:套利相关策略介绍章总.pdf|套利相关策略介绍_章总]] [[媒体文件:资管行业杨忆风 20160617.pdf|资管行业_杨忆风]] [[媒体文件:多因子量化模型简介_201600813.pdf |多因子模型_杨忆风]] [[媒体文件:汪洋-DQNStock.pdf | DQNStock_汪洋]]
|-
|2016-09-20 ||Deep Q-learning||Dong Wang || [http://arxiv.org/pdf/1509.02971v5.pdf paper1] [http://www.iclr.cc/lib/exe/fetch.php?media=iclr2015:silver-iclr2015.pdf slides]
|-
|2016-11-12 ||Generative Adversarial Nets||Yang Wang || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c9/Generative_adversarial_network.pdf slides]
|-
|2017-01-01 ||Deep Direct Reinforcement Learning for Financial Signal Representation and Trading||Yang Wang || [[媒体文件:07407387.pdf|paper]]
|-
|2017-02-08 ||Value Iteration Networks||Yang Wang || [[媒体文件:Value-iteration-networks.pdf|paper]]
|-
|2017-02-08 ||TOWARDS PRINCIPLED METHODS FOR TRAINING GENERATIVE ADVERSARIAL NETWORKS||Yang Wang || [[媒体文件:TOWARDS_PRINCIPLED_METHODS_FOR_TRAINING.pdf |paper]]
|-
|2017-02-08 ||Wasserstein GAN||Yang Wang || [[媒体文件:Wasserstein_GAN.pdf |paper]]
|-
|2017-02-13 ||UNDERSTANDING DEEP LEARNING REQUIRES RETHINKING GENERALIZATION||Yang Wang || [[媒体文件:UNDERSTANDING_DEEP_LEARNING_REQUIRES_RETHINKING_GENERALIZATION.pdf |paper]] [[媒体文件:Review_understanding_deep_learning_requires_rethinking_generalization.pdf | slides]]
|-
|2017-02-23 ||LEARNING TO ACT BY PREDICTING THE FUTURE||Yang Wang || [[媒体文件:LEARNING_TO_ACT_BY_PREDICTING_THE_FUTURE.pdf |paper]]
|-
|2017-06-01 ||Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures||Xin Jing || [[媒体文件:Dynamic Hedging - Kroner and Sultan (JFQA, 1993).pdf |paper]][[媒体文件:Slides_for_Dynamic_Hedage.pdf | slides]]
|-
|2017-06-01 ||A_clustering_time_series_model_for_the_optimal_hedge_ratio_decision_making||Wang Yaodong|| [[媒体文件:A_clustering_time_series_model_for_the_optimal_hedge_ratio_decision_making.pdf ‎ |paper]][[媒体文件:A_clustering_time_series_model_for_the_optimal_hedge_ratio.pptx | slides]]
|-
|2017-08-24 ||Understanding Black-box Predictions via Influence Functions||Yang Wang || [[媒体文件:Understanding_Black-box_Predictions_via_Influence_Functions.pdf |paper]][[媒体文件:Appendix_Understanding_Black-box_Predictions_via_Influence_Functions.pdf | appendix]]
|-
|2017-08-24 ||Supervised Principal Component Analysis: Visualization, Classification and Regression on Subspaces and Submanifolds||Yang Wang || [[媒体文件:Supervised_Principal_Component_Analysis-_Visualization%2C_Classification_and_Regression_on_Subspace_and_Submanifolds.pdf |paper]]
|-
|2017-11-05 ||Multi Factor Model||Yang Wang || [[媒体文件:20150426-国泰君安-数量化专题之五十七：基于组合权重优化的风格中性多因子选股策略.pdf |研报]] [[媒体文件:MSCI-CNE5-201309.pdf | CNE5]] [[媒体文件:MSCI-USE4-201109.pdf | CNE4]]
|}
|-
|2018-03-31 ||Portfolio Selection||Caixia Wang|| [[媒体文件:Http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/文件:Portfolio_Selection.pptx |研报]] [[媒体文件:MSCI-CNE5-201309.pdf | CNE5]] [[媒体文件:MSCI-USE4-201109.pdf | CNE4]]
|}

Finance-weekly-reading

2018-03-31T09:30:53Z

Wangcx：Http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/文件:Portfolio_Selection.pptx

Finance-weekly-reading

2018-03-31T09:27:40Z

Wangcx：

{|class='wikitable'
!Time !! Title !! Leader !! Paper
|-
|2015-08-03 ||Detect & Describe: Deep learning of bank stress in the news || Dong Wang || Samuel Ronnqvist, Peter Sarlin, arxiv 2015.07.25 [[http://arxiv.org/pdf/1507.07870.pdf pdf]]
|-
|2015-08-05 ||Analysis of Hidden Markov Models and Support vector machines in financial applications|| Rong Liu || Satish Rao Jerry Hong 2010[http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-63.pdf pdf]
|-
|2015-08-10 ||NEURAL NETWORKS APPLIED TO STOCK MARKET FORECASTING: AN EMPIRICAL ANALYSIS|| Yang Yu || Leandro Maciel, Rosangela Ballini 2010 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/7/76/NEURAL_NETWORKS_APPLIED_TO_STOCK_MARKET_FORECASTING_AN_EMPIRICAL_ANALYSIS.pdf pdf]
|-
|2015-08-12 ||A Decision Tree-Rough Set Hybrid System for Stock Market Trend Prediction|| Rong Liu || 2010 [http://www.ijcaonline.org/volume6/number9/pxc3871449.pdf pdf]
|-
|2015-08-12 ||A Comparision of Three Network Portfolio Selection Methods || Dong Wang || 2015 [http://arxiv.org/pdf/1512.01905.pdf pdf]
|-
|2016-06-12 ||Online Portfolio Selection: A Survey || Maoning Wang|| January 2014 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/9b/A35-li.pdf pdf]
|-
|2016-06-12 ||SEQUENTIALMONTECARLOSAMPLINGFORCORRELATEDLATENTLONG-MEMORY TIME-SERIE || Maoning Wang|| ICASSP 2016 [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b4/0006580.pdf pdf]
|-
|2016-06-17 ||PAMR: Passive Aggressive Mean Reversion Strategy for Portfolio Selection|| Author: LiBin|| Machine Learning May 2012, Volume 87, Issue 2, pp 221-258 [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.421.579&rep=rep1&type=pdf pdf]
|-
|2016-06-17 ||随机微分方程简介|| Author: 陈堰平|| ppt 2008年12月14日 [http://cos.name/wp-content/uploads/2008/12/stochastic-differential-equation-with-r.pdf pdf]
|-
|2016-06-24 ||Where are contrarian profits due to stock market overreaction|| Caixia Wang|| [http://www.finance.martinsewell.com/stylized-facts/dependence/LoMacKinlay1990.pdf pdf]
|-
|2016-07-16 ||Sentiment Analysis in Finance Market Forcast||Dong Wang || [http://wangd.cslt.org/talks/pdf/SentimentAnalysisinFinanceMarketForcast.pptx slides]
|-
|2016-08-20 ||经管量化分析研讨会|| -||[[媒体文件:套利相关策略介绍章总.pdf|套利相关策略介绍_章总]] [[媒体文件:资管行业杨忆风 20160617.pdf|资管行业_杨忆风]] [[媒体文件:多因子量化模型简介_201600813.pdf |多因子模型_杨忆风]] [[媒体文件:汪洋-DQNStock.pdf | DQNStock_汪洋]]
|-
|2016-09-20 ||Deep Q-learning||Dong Wang || [http://arxiv.org/pdf/1509.02971v5.pdf paper1] [http://www.iclr.cc/lib/exe/fetch.php?media=iclr2015:silver-iclr2015.pdf slides]
|-
|2016-11-12 ||Generative Adversarial Nets||Yang Wang || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/c/c9/Generative_adversarial_network.pdf slides]
|-
|2017-01-01 ||Deep Direct Reinforcement Learning for Financial Signal Representation and Trading||Yang Wang || [[媒体文件:07407387.pdf|paper]]
|-
|2017-02-08 ||Value Iteration Networks||Yang Wang || [[媒体文件:Value-iteration-networks.pdf|paper]]
|-
|2017-02-08 ||TOWARDS PRINCIPLED METHODS FOR TRAINING GENERATIVE ADVERSARIAL NETWORKS||Yang Wang || [[媒体文件:TOWARDS_PRINCIPLED_METHODS_FOR_TRAINING.pdf |paper]]
|-
|2017-02-08 ||Wasserstein GAN||Yang Wang || [[媒体文件:Wasserstein_GAN.pdf |paper]]
|-
|2017-02-13 ||UNDERSTANDING DEEP LEARNING REQUIRES RETHINKING GENERALIZATION||Yang Wang || [[媒体文件:UNDERSTANDING_DEEP_LEARNING_REQUIRES_RETHINKING_GENERALIZATION.pdf |paper]] [[媒体文件:Review_understanding_deep_learning_requires_rethinking_generalization.pdf | slides]]
|-
|2017-02-23 ||LEARNING TO ACT BY PREDICTING THE FUTURE||Yang Wang || [[媒体文件:LEARNING_TO_ACT_BY_PREDICTING_THE_FUTURE.pdf |paper]]
|-
|2017-06-01 ||Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures||Xin Jing || [[媒体文件:Dynamic Hedging - Kroner and Sultan (JFQA, 1993).pdf |paper]][[媒体文件:Slides_for_Dynamic_Hedage.pdf | slides]]
|-
|2017-06-01 ||A_clustering_time_series_model_for_the_optimal_hedge_ratio_decision_making||Wang Yaodong|| [[媒体文件:A_clustering_time_series_model_for_the_optimal_hedge_ratio_decision_making.pdf ‎ |paper]][[媒体文件:A_clustering_time_series_model_for_the_optimal_hedge_ratio.pptx | slides]]
|-
|2017-08-24 ||Understanding Black-box Predictions via Influence Functions||Yang Wang || [[媒体文件:Understanding_Black-box_Predictions_via_Influence_Functions.pdf |paper]][[媒体文件:Appendix_Understanding_Black-box_Predictions_via_Influence_Functions.pdf | appendix]]
|-
|2017-08-24 ||Supervised Principal Component Analysis: Visualization, Classification and Regression on Subspaces and Submanifolds||Yang Wang || [[媒体文件:Supervised_Principal_Component_Analysis-_Visualization%2C_Classification_and_Regression_on_Subspace_and_Submanifolds.pdf |paper]]
|-
|2017-11-05 ||Multi Factor Model||Yang Wang || [[媒体文件:20150426-国泰君安-数量化专题之五十七：基于组合权重优化的风格中性多因子选股策略.pdf |研报]] [[媒体文件:MSCI-CNE5-201309.pdf | CNE5]] [[媒体文件:MSCI-USE4-201109.pdf | CNE4]]
|}
|-
|2017-11-05 ||Portfolio Selection||Caixia Wang || [[媒体文件:http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Portfolio_Selection.pptx |研报]]
|}

文件:Portfolio Selection.pptx

2018-03-31T09:15:26Z

Wangcx：

FIN Status Report 2016-08-29

2016-08-29T05:39:47Z

Wangcx：

{| class="wikitable"
!People !! Last Week !! This Week
|-
|Caixia Wang
||
* Finished Chapter 5.
* Have been writing Chapter 10.
||
* Continue to write Chapter 10.
|-

|-
| Maoning Wang||
* CONTENT
||
* CONTENT
|-

|-
| Yang Wang||
* CONTENT
||
* CONTENT
|-

|}

FIN Status Report 2016-08-29

2016-08-29T02:09:41Z

Wangcx：以“ {| class="wikitable" !People !! Last Week !! This Week |- |Caixia Wang || * * || * |- |- | Maoning Wang|| * CONTENT || * CONTENT |- |- | Yang Wang|| *...”为内容创建页面

{| class="wikitable"
!People !! Last Week !! This Week
|-
|Caixia Wang
||
*
*
||
*
|-

|-
| Maoning Wang||
* CONTENT
||
* CONTENT
|-

|-
| Yang Wang||
* CONTENT
||
* CONTENT
|-

|}

FIN Status Report 2016-08-22

2016-08-22T07:41:20Z

Wangcx：

{| class="wikitable"
!People !! Last Week !! This Week
|-
|Caixia Wang ||
* Have been writing Chapter 5.
*Begin to write Chapter 10.
||
*Continue to do these work.
|-
|Maoning Wang ||
*read materials on Gaussian Processes and Dirichlet Process
*put down the lecture notes: Introduction--completed, Gaussian Processes--only a little is completed
||
*continue taking the summer-seminar notes
|-
|添加姓名 || ||
|}

FIN Status Report 2016-08-22

2016-08-22T07:40:58Z

Wangcx：

{| class="wikitable"
!People !! Last Week !! This Week
|-
|Caixia Wang ||
* Have been writing Chapter 5.
*Begin to write Chapter 10.
||
Continue to do these work.
|-
|Maoning Wang ||
*read materials on Gaussian Processes and Dirichlet Process
*put down the lecture notes: Introduction--completed, Gaussian Processes--only a little is completed
||
*continue taking the summer-seminar notes
|-
|添加姓名 || ||
|}

FIN Status Report 2016-08-22

2016-08-22T07:40:21Z

Wangcx：

{| class="wikitable"
!People !! Last Week !! This Week
|-
|Caixia Wang ||
1. Have been writing Chapter 5.
2. Begin to write Chapter 10.

||
Continue to do these work.
|-
|Maoning Wang ||
*read materials on Gaussian Processes and Dirichlet Process
*put down the lecture notes: Introduction--completed, Gaussian Processes--only a little is completed
||
*continue taking the summer-seminar notes
|-
|添加姓名 || ||
|}

2016 Summer Seminar for Machine learning

2016-08-19T02:04:28Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Owner !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || Dong Wang || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson1-2.mp4 video(part 2)][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || Aiting Liu; Aodong Li|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson2-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson2-2.mp4 video(part 2)] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || Aiting Liu || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson3-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson3-2.mp4 video(part 2)]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| Hang Luo; Jiyuan Zhang; Zhiyuan|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt4.%20Deep%20learning-1.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson4-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson4-2_Deep_learning.m4v video(part 2)] [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/12 ||Dong Wang || Deep learning (2)|| Hang Luo; Jiyuan Zhang; Zhiyuan || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson5-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson5-2_Deep_learning.m4v video(part 2)] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
|-
| 2016/07/13 || Caixia Wang || Kernel methods || Caixia;Ziwei || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/0/07/KM1.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson6_Kernel_method.m4v video] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
| 2016/07/18 ||Yang Feng || Graphical model (1) ||Jingyi Lin; Ying Shi; Yang Wang|| [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/d/dd/Chpt7._Graphical_models-bayesian_approach.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson7_Graphical_model.m4v video]
|-
| 2016/07/21 ||Dong Wang || Graphical model (2) ||Jingyi Lin; Ying Shi; Yang Wang||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt8.%20Graphical%20models-2.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson8-1_Graphical_model.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson8-2_Graphical_model.m4v video(part 2)] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/Graphical%20models-learningInference.pptx Yang's slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/GraphicalModel_Jordan.pdf Jordan's lecture]
|-
| 2016/07/25 ||Dong Wang || Unsupervised learning ||Lantian; Yixiang ||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt9.%20Unsupervised%20Learning.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson9-1_Unsupervised_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson9-2_Unsupervised_learning.m4v video(part 2)] [http://mlg.eng.cam.ac.uk/zoubin/papers/ul.pdf Unsupervised Learning from Zoubin Ghahramani, Cambridge] [http://www.mit.edu/~9.54/fall14/slides/Class13.pdf slides from MIT] [https://page.mi.fu-berlin.de/rojas/neural/chapter/K5.pdf Neural Networks - A Systematic Introduction, Raul Rojas] [http://www.cs.bu.edu/fac/gkollios/ada01/LectNotes/Clustering2.ppt slides from BU] [http://web.mit.edu/6.454/www/www_fall_2003/ihler/slides.pdf manifold slides from MIT]
|-
| 2016/07/26 ||Dong Wang || Non parametric models ||Maoning Wang; || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt10.%20Non-Parametric%20Learning.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson10-1_Nonparameteric_model.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson10-2_Nonparameteric_model.m4v video(part 2)] [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process] [http://stat.columbia.edu/~porbanz/npb-tutorial.html Resource for non-parametric Bayesian] [http://www.gatsby.ucl.ac.uk/~ywteh/research/npbayes/dp.pdf A good tutorial]
|-
| 2016/07/28 ||Maoning Wang || Evolutionary learning ||Maoning Wang; ||[http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:EA_%E7%8E%8B%E5%8D%AF%E5%AE%81.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson11_Evolutional_algorithm.m4v video][http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Introduction_to_Evolutionary_Computing.pdf Introduction_to_Evolutionary_Computing.pdf ‎]
|-
| 2016/07/29 ||Dong Wang || Reinforcement learning || Chao Xing || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt12.%20Reinforcement%20Learning.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/reinforcement1.mov video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/reinforcement2.mov video(part 2)] [http://www.jair.org/media/301/live-301-1562-jair.pdf an old but good review] [http://rll.berkeley.edu/deeprlcourse/ state-of-the-art course]
|-
| 2016/08/02 ||Dong Wang || Optimization || Caixia; ||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt13.%20Optimization.pptx slides] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt2.pdf Convex optimization II]
|-
|}

Caixia Wang 2016-08-15

2016-08-15T00:35:34Z

Wangcx：以“Last week: 1. learning Optimization. 2.writing Chapter 5 with Ziwei. This week: Continue to do our work.”为内容创建页面

Last week:

1. learning Optimization.

2.writing Chapter 5 with Ziwei.

This week:

Continue to do our work.

2016-08-15

2016-08-15T00:33:35Z

Wangcx：

[[Chao Xing 2016-08-15]]

[[Maoning Wang 2016-08-15]]

[[Ziwei Bai 2016-08-15]]

[[Aodong Li 2016-08-15]]

[[Yang Wang 2016-08-15]]

[[Zhiyong Zhang 2016-08-15]]

[[Jiyuan Zhang 2016-08-15]]

[[Zhiyuan Tang 2016-08-15]]

[[Ying Shi 2016-08-15]]

[[Caixia Wang 2016-08-15]]

2016-08-15

2016-08-15T00:33:19Z

Wangcx：

2016-08-08 Caixia Wang

2016-08-10T00:54:12Z

Wangcx：以“1. learned Optimization 2. wrote chapter 5 kernel methods section 5.1.”为内容创建页面

1. learned Optimization

2. wrote chapter 5 kernel methods section 5.1.

2016-08-08

2016-08-10T00:51:57Z

Wangcx：

[[2016-08-08 Mengyuan Zhao]]

[[2016-08-08 Chao Xing]]

[[2016-08-08 Maoning Wang]]

[[2016-08-08 Ziwei Bai]]

[[2016-08-08 Ying Shi]]

[[2016-08-08 Jiyuan Zhang]]

[[2016-08-08 Aodong Li]]

[[2016-08-08 Zhiyong Zhang]]

[[2016-08-08 Yang Wang]]

[[2016-08-08 Lantian Li]]

[[2016-08-08 Zhiyuan Tang]]

[[2016-08-08 Yang Feng]]

[[2016-08-08 Hang Luo]]

[[2016-08-08 Caixia Wang]]

Caixia Wang 2016-08-01

2016-08-03T08:17:39Z

Wangcx：以“last week: 1. Reading book "Convex Optimization ". 2. Prepare chapter 5 kernel methods. this week: 1. continue reading book "Convex Optimization ". 2. begin to...”为内容创建页面

last week:

1. Reading book "Convex Optimization ".

2. Prepare chapter 5 kernel methods.

this week:

1. continue reading book "Convex Optimization ".

2. begin to writing chapter 5 kernel methods.

2016-08-01

2016-08-03T08:12:53Z

Wangcx：

[[The Lab 2016-08-01]]

[[Chao Xing 2016-08-01]]

[[Lantian Li 2016-08-01]]

[[Andi Zhang 2016-08-01]]

[[Maoning Wang 2016-08-01]]

[[Ying Shi 2016-08-01]]

[[Zhiyuan Tang 2016-08-01]]

[[Yang Wang 2016-08-01]]

[[Aodong Li 2016-08-01]]

[[Yang Feng 2016-08-01]]

[[Mengyuan Zhao 2016-08-01]]

[[Jiyuan Zhang 2016-08-01]]

[[Zhiyong Zhang 2016-08-01]]

[[Caixia Wang 2016-08-01]]

Caixia Wang 2016-07-25

2016-07-25T00:25:44Z

Wangcx：以“last week: 1.read the book "Deep learning" Chapter12-19 2.learn convex optimization this week: 1.convex optimization 2.kernel methods”为内容创建页面

last week:

1.read the book "Deep learning" Chapter12-19

2.learn convex optimization

this week:

1.convex optimization

2.kernel methods

2016-07-25

2016-07-25T00:23:02Z

Wangcx：

[[Maoning Wang 2016-07-25]]

[[Aodong li 2016-07-25]]

[[Yang Wang 2016-07-25]]

[[Zhiyong Zhang 2016-07-25]]

[[Caixia Wang 2016-07-25]]

2016-07-25

2016-07-25T00:22:35Z

Wangcx：

[[Maoning Wang 2016-07-25]]

[[Aodong li 2016-07-25]]

[[Yang Wang 2016-07-25]]

[[Zhiyong Zhang 2016-07-25]]

[[Caixia Wang 2016-07-25]]

2016 Summer Seminar for Machine learning

2016-07-22T11:14:31Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Owner !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson1-2.mp4 video(part 2)][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || Aiting Liu; Aodong Li|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson2-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson2-2.mp4 video(part 2)] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson3-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson3-2.mp4 video(part 2)]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| Hang Luo; Jiyuan Zhang; Zhiyuan|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt4.%20Deep%20learning-1.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson4-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson4-2_Deep_learning.m4v video(part 2)] [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/12 ||Dong Wang || Deep learning (2)|| Hang Luo; Jiyuan Zhang; Zhiyuan || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson5-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson5-2_Deep_learning.m4v video(part 2)] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
|-
| 2016/07/13 || Caixia Wang || Kernel methods || Caixia; || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/0/07/KM1.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson6_Kernel_method.m4v video] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
| 2016/07/18 ||Yang Feng || Graphical model (1) ||Jingyi Lin; Ying Shi; Yang Wang|| [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/d/dd/Chpt7._Graphical_models-bayesian_approach.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson7_Graphical_model.m4v video]
|-
| 2016/07/21 ||Dong Wang || Graphical model (2) ||Jingyi Lin; Ying Shi; Yang Wang||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt%208.%20Graphical%20models-2.pptx slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/Graphical%20models-learningInference.pptx Yang's slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/GraphicalModel_Jordan.pdf Jordan's lecture]
|-
| 2016/07/25 ||Dong Wang || Unsupervised learning || ||
|-
| 2016/07/26 ||Dong Wang || Non parametric models ||Maoning Wang; || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/27 ||Dong Wang || Reinforcement learning || ||
|-
| 2016/07/28 ||Maoning Wang || Evolutionary learning ||Maoning Wang; ||
|-
| 2016/07/29 ||Dong Wang || Optimization || Caixia; || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

2016 Summer Seminar for Machine learning

2016-07-22T11:14:11Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Owner !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson1-2.mp4 video(part 2)][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || Aiting Liu; Aodong Li|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson2-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson2-2.mp4 video(part 2)] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson3-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson3-2.mp4 video(part 2)]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| Hang Luo; Jiyuan Zhang; Zhiyuan|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt4.%20Deep%20learning-1.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson4-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson4-2_Deep_learning.m4v video(part 2)] [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/12 ||Dong Wang || Deep learning (2)|| Hang Luo; Jiyuan Zhang; Zhiyuan || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson5-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson5-2_Deep_learning.m4v video(part 2)] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
|-
| 2016/07/13 || Caixia Wang || Kernel methods || Caixia; || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/0/07/KM1.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson6_Kernel_method.m4v video] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
| 2016/07/18 ||Yang Feng || Graphical model (1) ||Jingyi Lin; Ying Shi; Yang Wang|| [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/d/dd/Chpt7._Graphical_models-bayesian_approach.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson7_Graphical_model.m4v video]
|-
| 2016/07/21 ||Dong Wang || Graphical model (2) ||Jingyi Lin; Ying Shi; Yang Wang||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt%208.%20Graphical%20models-2.pptx slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/Graphical%20models-learningInference.pptx Yang's slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/GraphicalModel_Jordan.pdf Jordan's lecture]
|-
| 2016/07/25 ||Dong Wang || Unsupervised learning || ||
|-
| 2016/07/26 ||Dong Wang || Non parametric models ||Maoning Wang; || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/27 ||Dong Wang || Reinforcement learning || ||
|-
| 2016/07/28 ||Maoning Wang || Evolutionary learning ||Maoning Wang; ||
|-
| 2016/07/29 ||Dong Wang || Optimization || Caixia Wang/ || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

2016 Summer Seminar for Machine learning

2016-07-22T08:15:49Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Owner !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson1-2.mp4 video(part 2)][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || Aiting Liu; Aodong Li|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson2-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson2-2.mp4 video(part 2)] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson3-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson3-2.mp4 video(part 2)]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| Hang Luo; Jiyuan Zhang; Zhiyuan|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt4.%20Deep%20learning-1.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson4-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson4-2_Deep_learning.m4v video(part 2)] [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/12 ||Dong Wang || Deep learning (2)|| Hang Luo; Jiyuan Zhang; Zhiyuan || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson5-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson5-2_Deep_learning.m4v video(part 2)] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
|-
| 2016/07/13 ||Caixia Wang || Kernel methods || Caixia; || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/0/07/KM1.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson6_Kernel_method.m4v video] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
| 2016/07/18 ||Yang Feng || Graphical model (1) ||Jingyi Lin; Ying Shi; Yang Wang|| [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/d/dd/Chpt7._Graphical_models-bayesian_approach.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson7_Graphical_model.m4v video]
|-
| 2016/07/21 ||Dong Wang || Graphical model (2) ||Jingyi Lin; Ying Shi; Yang Wang||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt%208.%20Graphical%20models-2.pptx slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/Graphical%20models-learningInference.pptx Yang's slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/GraphicalModel_Jordan.pdf Jordan's lecture]
|-
| 2016/07/25 ||Dong Wang || Unsupervised learning || ||
|-
| 2016/07/26 ||Dong Wang || Non parametric models ||Maoning Wang; || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/27 ||Dong Wang || Reinforcement learning || ||
|-
| 2016/07/28 ||Maoning Wang || Evolutionary learning ||Maoning Wang; ||
|-
| 2016/07/29 ||Dong Wang || Optimization || || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

2016 Summer Seminar for Machine learning

2016-07-22T08:14:21Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Owner !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson1-2.mp4 video(part 2)][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || Aiting Liu; Aodong Li|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson2-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson2-2.mp4 video(part 2)] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson3-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson3-2.mp4 video(part 2)]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| Hang Luo Jiyuan Zhang [Zhiyuan]|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt4.%20Deep%20learning-1.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson4-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson4-2_Deep_learning.m4v video(part 2)] [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/12 ||Dong Wang || Deep learning (2)|| Hang Luo Jiyuan Zhang [Zhiyuan]|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson5-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson5-2_Deep_learning.m4v video(part 2)] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
|-
| 2016/07/13 ||Caixia Wang || Kernel methods || Caixia || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/0/07/KM1.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson6_Kernel_method.m4v video] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
| 2016/07/18 ||Yang Feng || Graphical model (1) ||Jingyi Lin Ying Shi Yang Wang|| [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/d/dd/Chpt7._Graphical_models-bayesian_approach.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson7_Graphical_model.m4v video]
|-
| 2016/07/21 ||Dong Wang || Graphical model (2) ||Jingyi Lin Ying Shi Yang Wang||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt%208.%20Graphical%20models-2.pptx slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/Graphical%20models-learningInference.pptx Yang's slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/GraphicalModel_Jordan.pdf Jordan's lecture]
|-
| 2016/07/25 ||Dong Wang || Unsupervised learning || ||
|-
| 2016/07/26 ||Dong Wang || Non parametric models ||Maoning Wang/ || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/27 ||Dong Wang || Reinforcement learning || ||
|-
| 2016/07/28 ||Maoning Wang || Evolutionary learning ||Maoning Wang/ ||
|-
| 2016/07/29 ||Dong Wang || Optimization || || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

2016 Summer Seminar for Machine learning

2016-07-22T06:44:00Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Owner !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson1-2.mp4 video(part 2)][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || Aiting Liu|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson2-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson2-2.mp4 video(part 2)] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson3-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson3-2.mp4 video(part 2)]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| Zhiyuan Hang Luo Jiyuan Zhang|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt4.%20Deep%20learning-1.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson4-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson4-2_Deep_learning.m4v video(part 2)] [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/12 ||Dong Wang || Deep learning (2)|| Zhiyuan Hang Luo Jiyuan Zhang || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson5-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson5-2_Deep_learning.m4v video(part 2)] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
|-
| 2016/07/13 ||Caixia Wang || Kernel methods || Caixia || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/0/07/KM1.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson6_Kernel_method.m4v video] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
| 2016/07/18 ||Yang Feng || Graphical model (1) ||Jingyi Lin Ying Shi Yang Wang|| [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/d/dd/Chpt7._Graphical_models-bayesian_approach.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson7_Graphical_model.m4v video]
|-
| 2016/07/21 ||Dong Wang || Graphical model (2) ||Jingyi Lin Ying Shi Yang Wang||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt%208.%20Graphical%20models-2.pptx slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/Graphical%20models-learningInference.pptx Yang's slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/GraphicalModel_Jordan.pdf Jordan's lecture]
|-
| 2016/07/25 ||Dong Wang || Unsupervised learning || ||
|-
| 2016/07/26 ||Dong Wang || Non parametric models || || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/27 ||Dong Wang || Reinforcement learning || ||
|-
| 2016/07/28 ||Maoning Wang || Evolutionary learning || ||
|-
| 2016/07/29 ||Dong Wang || Optimization || || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

2016 Summer Seminar for Machine learning

2016-07-22T06:14:56Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Owner !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson1-2.mp4 video(part 2)][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson2-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson2-2.mp4 video(part 2)] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson3-1.mp4 video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson3-2.mp4 video(part 2)]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| Zhiyuan Caixia || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt4.%20Deep%20learning-1.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson4-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson4-2_Deep_learning.m4v video(part 2)] [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/12 ||Dong Wang || Deep learning (2)|| Zhiyuan Caixia || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson5-1_Deep_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson5-2_Deep_learning.m4v video(part 2)] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
|-
| 2016/07/13 ||Caixia Wang || Kernel methods || || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/0/07/KM1.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson6_Kernel_method.m4v video] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
| 2016/07/18 ||Yang Feng || Graphical model (1) || || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/d/dd/Chpt7._Graphical_models-bayesian_approach.pdf slides] [http://arch.cslt.org/video/2016/sum-ML/lesson7_Graphical_model.m4v video]
|-
| 2016/07/21 ||Dong Wang || Graphical model (2) || ||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt%208.%20Graphical%20models-2.pptx slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/Graphical%20models-learningInference.pptx Yang's slides] [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chapt8/GraphicalModel_Jordan.pdf Jordan's lecture]
|-
| 2016/07/25 ||Dong Wang || Unsupervised learning || ||
|-
| 2016/07/26 ||Dong Wang || Non parametric models || || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/27 ||Dong Wang || Reinforcement learning || ||
|-
| 2016/07/28 ||Maoning Wang || Evolutionary learning || ||
|-
| 2016/07/29 ||Dong Wang || Optimization || || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

Caixia Wang 2016-07-18

2016-07-18T09:24:00Z

Wangcx：以“last week: 1. Chapter11 Practical Methodology. 2.Chapter12 Applications. 3.Chapter13 Linear Factor Models. 4.Chapter14 Autoencoders. 5.Give a talk about Kernel...”为内容创建页面

last week:

1. Chapter11 Practical Methodology.

2.Chapter12 Applications.

3.Chapter13 Linear Factor Models.

4.Chapter14 Autoencoders.

5.Give a talk about Kernel Methods.

6.Check Zhiyuan Tang's paper.

this week:

Finish the rest of deep learning.

2016-07-18

2016-07-18T09:15:30Z

Wangcx：

[[Mengyuan Zhao 2016-07-18]]

[[Ying Shi 2016-07-18]]

[[Zhiyong Zhang 2016-07-18]]

[[Maoning Wang 2016-07-18]]

[[Yang Wang 2016-07-18]]

[[Ziwei Bai 2016-07-18]]

[[Jiyuan Zhang 2016-07-18]]

[[Zhiyuan Tang 2016-07-18]]

[[Lantian Li 2016-07-18]]

[[Yang Feng 2016-07-18]]

[[Chao Xing 2016-07-18]]

[[Caixia Wang 2016-07-18]]

2016 Summer Seminar for Machine learning

2016-07-14T03:10:26Z

Wangcx：

2016 Summer Seminar for Machine learning

2016-07-13T06:11:19Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson1-2.mp4 video(part 2)][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt4.%20Deep%20learning-1.pptx slides] [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/12 ||Dong Wang || Deep learning (2)|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
|-
| 2016/07/13 ||Caixia Wang || Kernel methods || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/0/07/KM1.pdf slides] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
|2016/07/ ||Dong Wang || Unsupervised learning ||
|-
| 2016/07/ ||Dong Wang || Probabilistic learning theory||
|-
| 2016/07/ ||Yang Feng || Graphical model: Bayesian approach ||
|-
| 2016/07/ ||Yang Feng || Graphical model: Random field ||
|-
| 2016/07/ ||Dong Wang || No parametric models || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/ ||Dong Wang || Reinforcement learning ||
|-
| 2016/07/ ||Maoning Wang || Evolutionary learning ||
|-
| 2016/07/ ||Dong Wang || Optimization || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

文件:KM1.pdf

2016-07-13T06:09:45Z

Wangcx：kerenl methods

kerenl methods

2016 Summer Seminar for Machine learning

2016-07-13T06:08:48Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://arch.cslt.org/video/2016/sum-ML/lesson1-2.mp4 video(part 2)][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt4.%20Deep%20learning-1.pptx slides] [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/12 ||Dong Wang || Deep learning (2)|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
|-
| 2016/07/13 ||Caixia Wang || Kernel methods || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
|2016/07/ ||Dong Wang || Unsupervised learning ||
|-
| 2016/07/ ||Dong Wang || Probabilistic learning theory||
|-
| 2016/07/ ||Yang Feng || Graphical model: Bayesian approach ||
|-
| 2016/07/ ||Yang Feng || Graphical model: Random field ||
|-
| 2016/07/ ||Dong Wang || No parametric models || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/ ||Dong Wang || Reinforcement learning ||
|-
| 2016/07/ ||Maoning Wang || Evolutionary learning ||
|-
| 2016/07/ ||Dong Wang || Optimization || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

2016 Summer Seminar for Machine learning

2016-07-11T08:30:57Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/08 ||Dong Wang || Neural networks || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides]
|-
| 2016/07/11 ||Dong Wang || Deep learning (1)|| [http://www.iro.umontreal.ca/~bengioy/talks/DL-Tutorial-NIPS2015.pdf NIPS 2015 tutorial]
|-
| 2016/07/ ||Dong Wang || Deep learning (2)||
|-
| 2016/07/ ||Dong Wang || Unsupervised learning ||
|-
| 2016/07/ ||Caixia Wang || Kernel methods || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
| 2016/07/ ||Dong Wang || Probabilistic learning theory||
|-
| 2016/07/ ||Yang Feng || Graphical model: Bayesian approach ||
|-
| 2016/07/ ||Yang Feng || Graphical model: Random field ||
|-
| 2016/07/ ||Dong Wang || No parametric models || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/ ||Dong Wang || Reinforcement learning ||
|-
| 2016/07/ ||Maoning Wang || Evolutionary learning ||
|-
| 2016/07/ ||Dong Wang || Optimization || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

Caixia Wang 2016-07-11

2016-07-11T00:15:29Z

Wangcx：以“1、Kernel Methods for Pattern Analysis 2、Pattern Recognition and Machine Learning 6-7”为内容创建页面

1、Kernel Methods for Pattern Analysis

2、Pattern Recognition and Machine Learning 6-7

2016-07-11

2016-07-11T00:13:05Z

Wangcx：

[[Yang Feng 2016-07-11]]

[[Mengyuan Zhao 2016-07-11]]

[[Lantian Li 2016-07-11]]

[[Ziwei Bai 2016-07-11]]

[[Caixia Wang 2016-07-11]]

2016 Summer Seminar for Machine learning

2016-07-06T08:29:08Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/ ||Dong Wang || Neural networks ||
|-
| 2016/07/ ||Dong Wang || Deep learning (1)||
|-
| 2016/07/ ||Dong Wang || Deep learning (2)||
|-
| 2016/07/ ||Dong Wang || Unsupervised learning ||
|-
| 2016/07/ ||Caixia Wang || Kernel methods || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/9/95/Pattern_Recognition_and_Machine_Learning.pdf pattern recognition 6-7]
|-
| 2016/07/ ||Dong Wang || Probabilistic learning theory||
|-
| 2016/07/ ||Yang Feng || Graphical model: Bayesian approach ||
|-
| 2016/07/ ||Yang Feng || Graphical model: Random field ||
|-
| 2016/07/ ||Dong Wang || No parametric models || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/ ||Dong Wang || Reinforcement learning ||
|-
| 2016/07/ ||Maoning Wang || Evolutionary learning ||
|-
| 2016/07/ ||Dong Wang || Optimization || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

文件:Pattern Recognition and Machine Learning.pdf

2016-07-06T08:22:40Z

Wangcx：

2016 Summer Seminar for Machine learning

2016-07-06T08:22:01Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/ ||Dong Wang || Neural networks ||
|-
| 2016/07/ ||Dong Wang || Deep learning (1)||
|-
| 2016/07/ ||Dong Wang || Deep learning (2)||
|-
| 2016/07/ ||Dong Wang || Unsupervised learning ||
|-
| 2016/07/ ||Caixia Wang || Kernel methods || [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/b/b5/Kernel_Methods_for_Pattern_Analysis.pdf Kernel method book]
|-
| 2016/07/ ||Dong Wang || Probabilistic learning theory||
|-
| 2016/07/ ||Yang Feng || Graphical model: Bayesian approach ||
|-
| 2016/07/ ||Yang Feng || Graphical model: Random field ||
|-
| 2016/07/ ||Dong Wang || No parametric models || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/ ||Dong Wang || Reinforcement learning ||
|-
| 2016/07/ ||Maoning Wang || Evolutionary learning ||
|-
| 2016/07/ ||Dong Wang || Optimization || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

2016 Summer Seminar for Machine learning

2016-07-06T03:08:11Z

Wangcx：

2016 Summer Seminar for Machine learning

2016-07-06T03:07:35Z

Wangcx：

2016 Summer Seminar for Machine learning

2016-07-06T02:59:54Z

Wangcx：

2016 Summer Seminar for Machine learning

2016-07-06T02:53:17Z

Wangcx：

*Location: FIT-1-304

{| class="wikitable"
! Date !! Speaker!! Title !! Materials
|-
| 2016/07/04 ||Dong Wang || Machine learning overview || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt1.%20Overview%20of%20Machine%20Learning.pptx slides][http://cs229.stanford.edu/section/cs229-linalg.pdf Algebra review] [http://cs229.stanford.edu/section/cs229-prob.pdf probability review] [http://cs229.stanford.edu/section/gaussians.pdf Gaussian distribution][http://cs229.stanford.edu/notes/cs229-notes4.pdf Learning theory]
|-
| 2016/07/05 ||Dong Wang || Linear models || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt2.%20Linear%20Model.pptx slides] [http://cs229.stanford.edu/notes/cs229-notes1.pdf NG's lecture 1] [http://cs229.stanford.edu/notes/cs229-notes2.pdf NG's lecture 2]
|-
| 2016/07/ ||Dong Wang || Neural networks ||
|-
| 2016/07/ ||Dong Wang || Deep learning (1)||
|-
| 2016/07/ ||Dong Wang || Deep learning (2)||
|-
| 2016/07/ ||Dong Wang || Unsupervised learning ||
|-
| 2016/07/ ||Caixia Wang || Kernel methods || http://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/文件:Kernel_Methods_for_Pattern_Analysis.pdf Kernel methods]
|-
| 2016/07/ ||Dong Wang || Probabilistic learning theory||
|-
| 2016/07/ ||Yang Feng || Graphical model: Bayesian approach ||
|-
| 2016/07/ ||Yang Feng || Graphical model: Random field ||
|-
| 2016/07/ ||Dong Wang || No parametric models || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
|-
| 2016/07/ ||Dong Wang || Reinforcement learning ||
|-
| 2016/07/ ||Maoning Wang || Evolutionary learning ||
|-
| 2016/07/ ||Dong Wang || Optimization || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
|-
|}

文件:Kernel Methods for Pattern Analysis.pdf

2016-07-06T02:50:40Z

Wangcx：

Caixia Wang 2016-07-04

2016-07-04T00:48:21Z

Wangcx：以“ Last week: 1. Convolutional Networks 2. Sequence Modeling:. RNN This week: Two chapters”为内容创建页面

Last week:

1. Convolutional Networks

2. Sequence Modeling:. RNN

This week:

Two chapters

2016-07-04

2016-07-04T00:45:18Z

Wangcx：

[[Chao Xing 2016-07-04]]

[[Maoning Wang 2016-07-04]]

[[Jiyuan Zhang 2016-07-04]]

[[Mengyuan Zhao 2016-07-04]]

[[Zhiyuan Tang 2016-07-04]]

[[Zhiyong Zhang 2016-07-04]]

[[Caixia Wang 2016-07-04]]