“2016 Summer Seminar for Machine learning”版本间的差异
来自cslt Wiki
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{| class="wikitable" | {| class="wikitable" | ||
− | ! Date !! Speaker!! Title !! Materials | + | ! Date !! Speaker!! Title !! Ower !! Materials |
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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] | + | | 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] | + | | 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] | + | | 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] | + | | 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] | + | | 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] | + | | 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 || | + | | 2016/07/ ||Yang Feng || Graphical model: Bayesian approach || Jingyi Lin || |
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− | | 2016/07/ ||Yang Feng || Graphical model: Random field || | + | | 2016/07/ ||Yang Feng || Graphical model: Random field || || |
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− | | 2016/07/ ||Dong Wang || Unsupervised learning || | + | | 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] | + | | 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 || | + | | 2016/07/ ||Dong Wang || Reinforcement learning || || |
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− | | 2016/07/ ||Maoning Wang || Evolutionary learning || | + | | 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] | + | | 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 |