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

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| 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]
 
| 2016/07/26    ||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 ||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://cslt.riit.tsinghua.edu.cn/mediawiki/index.php/%E6%96%87%E4%BB%B6:Introduction_to_Evolutionary_Computing.pdf]
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| 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://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 ||  Chao Xing ||
 
| 2016/07/29    ||Dong Wang  || Reinforcement learning ||  Chao Xing ||

2016年7月28日 (四) 12:01的版本

  • Location: FIT-1-304


Date Speaker Title Owner Materials
2016/07/04 Dong Wang Machine learning overview Dong Wang slidesvideo(part 2)Algebra review probability review Gaussian distributionLearning theory
2016/07/05 Dong Wang Linear models Aiting Liu; Aodong Li slides video(part 1) video(part 2) NG's lecture 1 NG's lecture 2
2016/07/08 Dong Wang Neural networks Aiting Liu slides video(part 1) video(part 2)
2016/07/11 Dong Wang Deep learning (1) Hang Luo; Jiyuan Zhang; Zhiyuan slides video(part 1) video(part 2) NIPS 2015 tutorial
2016/07/12 Dong Wang Deep learning (2) Hang Luo; Jiyuan Zhang; Zhiyuan slides video(part 1) video(part 2) Li Deng's ICASSP16 keynote
2016/07/13 Caixia Wang Kernel methods Caixia;Ziwei slides video Kernel method book pattern recognition 6-7
2016/07/18 Yang Feng Graphical model (1) Jingyi Lin; Ying Shi; Yang Wang slides video
2016/07/21 Dong Wang Graphical model (2) Jingyi Lin; Ying Shi; Yang Wang slides video(part 1) video(part 2) Yang's slides Jordan's lecture
2016/07/25 Dong Wang Unsupervised learning slides video(part 1) video(part 2) Unsupervised Learning from Zoubin Ghahramani, Cambridge slides from MIT Neural Networks - A Systematic Introduction, Raul Rojas slides from BU manifold slides from MIT
2016/07/26 Dong Wang Non parametric models Maoning Wang; slides video(part 1) video(part 2) Gaussian process Resource for non-parametric Bayesian A good tutorial
2016/07/28 Maoning Wang Evolutionary learning Maoning Wang; slides Introduction_to_Evolutionary_Computing.pdf ‎
2016/07/29 Dong Wang Reinforcement learning Chao Xing
2016/08/01 Dong Wang Optimization Caixia; Convex optimization I Convex optimization II