“2016 Summer Seminar for Machine learning”版本间的差异

来自cslt Wiki
跳转至: 导航搜索
第8行: 第8行:
 
| 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]
 
| 2016/07/04  ||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 || Aodong Lantian|| [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]
+
| 2016/07/05  ||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 || Jiyuan Zhang || [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)]
+
| 2016/07/08    ||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]
+
| 2016/07/11    ||Dong Wang  || Deep learning (1)|| || [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]
+
| 2016/07/12  ||Dong Wang  || Deep learning (2)||  || [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 || Ziwei Bai || [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]
+
| 2016/07/13    ||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) || Jingyi Lin || [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]  
+
| 2016/07/18    ||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) || Ying Shi ||[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]
+
| 2016/07/21    ||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 || Zhiyong Zhang ||
+
| 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]
+
| 2016/07/26    ||Dong Wang  || Non parametric models || || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
 
|-
 
|-
| 2016/07/27    ||Dong Wang  || Reinforcement learning || Chao Xing ||
+
| 2016/07/27    ||Dong Wang  || Reinforcement learning || ||
 
|-
 
|-
 
| 2016/07/28    ||Maoning Wang  || Evolutionary learning || ||
 
| 2016/07/28    ||Maoning Wang  || Evolutionary learning || ||
 
|-
 
|-
| 2016/07/29    ||Dong Wang  || Optimization || Aiting Liu || [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization II]
+
| 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年7月22日 (五) 06:11的版本

  • Location: FIT-1-304


Date Speaker Title Owner Materials
2016/07/04 Dong Wang Machine learning overview slidesvideo(part 2)Algebra review probability review Gaussian distributionLearning theory
2016/07/05 Dong Wang Linear models slidesvideo(part 1) video(part 2) NG's lecture 1 NG's lecture 2
2016/07/08 Dong Wang Neural networks slides video(part 1) video(part 2)
2016/07/11 Dong Wang Deep learning (1) slides video(part 1) video(part 2) NIPS 2015 tutorial
2016/07/12 Dong Wang Deep learning (2) slides video(part 1) video(part 2) Li Deng's ICASSP16 keynote
2016/07/13 Caixia Wang Kernel methods slides video Kernel method book pattern recognition 6-7
2016/07/18 Yang Feng Graphical model (1) slides video
2016/07/21 Dong Wang Graphical model (2) slides Yang's slides Jordan's lecture
2016/07/25 Dong Wang Unsupervised learning
2016/07/26 Dong Wang Non parametric models Gaussian process
2016/07/27 Dong Wang Reinforcement learning
2016/07/28 Maoning Wang Evolutionary learning
2016/07/29 Dong Wang Optimization Convex optimization I Convex optimization II