“2016 Summer Seminar for Machine learning”版本间的差异
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(以“ *Location: FIT-1-304 {| class="wikitable" ! Date !! Speaker!! Title !! Materials !! |- | 2016/07/04 ||Dong Wang || Machine learning overview || |- | 2016/07/0...”为内容创建页面) |
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− | ! Date !! Speaker!! Title !! | + | ! Date !! Speaker!! Title !! Owner !! Materials |
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− | | 2016/07/04 ||Dong Wang || Machine learning overview || | + | | 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] |
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− | | 2016/07/05 ||Dong Wang || Linear models || | + | | 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] |
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− | | 2016/07/ ||Dong Wang || | + | | 2016/07/08 ||Dong Wang || Neural networks || Xing Chao; Aiting Liu; Andy Zhang; 白紫薇|| [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)] |
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− | | 2016/07/ ||Dong Wang || | + | | 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] |
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− | | 2016/07/ | + | | 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] |
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− | | 2016/07/ || | + | | 2016/07/13 || Caixia Wang || Kernel methods || Caixia;Ziwei || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt6.%20kernel%20method.pptx 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] |
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− | | 2016/07/ || | + | | 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] |
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− | | 2016/07/ ||Dong Wang || | + | | 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] |
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− | | 2016/07/ ||Dong Wang || | + | | 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] |
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− | | 2016/07/ ||Dong Wang || | + | | 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] |
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+ | | 2016/07/28 ||Maoning Wang || Evolutionary learning ||Dong 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 ] | ||
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+ | | 2016/07/29 ||Dong Wang || Reinforcement learning || Dong Wang || [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt12.%20Reinforcement%20Learning.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson12-1_Reinforcement_learning.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson12-2_Reinforcement_learning.m4v 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] | ||
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+ | | 2016/08/02 ||Dong Wang || Optimization || Caixia; ||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt13.%20Optimization.pptx slides] [http://arch.cslt.org/video/2016/sum-ML/lesson13-1_Optimization.m4v video(part 1)] [http://arch.cslt.org/video/2016/sum-ML/lesson13-2_Optimization.m4v video(part 2)] [http://cs229.stanford.edu/section/cs229-cvxopt.pdf Convex optimization I] [http://cs229.stanford.edu/section/cs229-cvxopt2.pdf Convex optimization II] | ||
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2017年1月6日 (五) 09:42的最后版本
- Location: FIT-1-304