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

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| 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]
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| 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]
 
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| 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]
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| 2016/07/05  ||Dong Wang  || Linear models || Aodong Li || [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]
 
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| 2016/07/08    ||Dong Wang  || Neural networks || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides]  
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| 2016/07/08    ||Dong Wang  || Neural networks || Jiyuan Zhang || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt3.%20Neural%20Network.pptx slides]  
 
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| 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]
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| 2016/07/11    ||Dong Wang  || Deep learning (1)|| Caixia Wang, Zhiyuan Tang || [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]
 
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| 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]
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| 2016/07/12  ||Dong Wang  || Deep learning (2)|| Caixia Wang, Zhiyuan Tang || [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]
 
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| 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]
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| 2016/07/13    ||Caixia Wang  || Kernel methods || Ziwei Bai || [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]
 
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| 2016/07/    ||Yang Feng  || Graphical model: Bayesian approach ||  
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| 2016/07/    ||Yang Feng  || Graphical model: Bayesian approach || Jingyi Lin ||
 
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| 2016/07/    ||Yang Feng  || Graphical model: Random field ||  
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| 2016/07/    ||Yang Feng  || Graphical model: Random field || ||
 
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| 2016/07/    ||Dong Wang  || Unsupervised learning ||  
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| 2016/07/    ||Dong Wang  || Unsupervised learning || ||
 
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| 2016/07/    ||Dong Wang  || Non parametric models || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
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| 2016/07/    ||Dong Wang  || Non parametric models || || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process]
 
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| 2016/07/    ||Dong Wang  || Reinforcement learning ||  
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| 2016/07/    ||Dong Wang  || Reinforcement learning || ||
 
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| 2016/07/    ||Maoning Wang  || Evolutionary learning ||  
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| 2016/07/    ||Maoning Wang  || Evolutionary learning || ||
 
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| 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]
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| 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]
 
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2016年7月14日 (四) 03:06的版本

  • Location: FIT-1-304


Date Speaker Title Ower 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 Aodong Li slides NG's lecture 1 NG's lecture 2
2016/07/08 Dong Wang Neural networks Jiyuan Zhang slides
2016/07/11 Dong Wang Deep learning (1) Caixia Wang, Zhiyuan Tang slides NIPS 2015 tutorial
2016/07/12 Dong Wang Deep learning (2) Caixia Wang, Zhiyuan Tang slides Li Deng's ICASSP16 keynote
2016/07/13 Caixia Wang Kernel methods Ziwei Bai slides Kernel method book pattern recognition 6-7
2016/07/ Yang Feng Graphical model: Bayesian approach Jingyi Lin
2016/07/ Yang Feng Graphical model: Random field
2016/07/ Dong Wang Unsupervised learning
2016/07/ Dong Wang Non parametric models Gaussian process
2016/07/ Dong Wang Reinforcement learning
2016/07/ Maoning Wang Evolutionary learning
2016/07/ Dong Wang Optimization Convex optimization I Convex optimization II
取自“http://cslt.org/mediawiki/index.php?title=2016_Summer_Seminar_for_Machine_learning&oldid=21108”