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

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| 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]  
 
| 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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| 2016/07/25    ||Dong Wang  || Unsupervised learning || ||[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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| 2016/07/25    ||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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| 2016/07/26    ||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]

2016年8月19日 (五) 02:04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 Lantian; Yixiang 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 videoIntroduction_to_Evolutionary_Computing.pdf ‎
2016/07/29 Dong Wang Reinforcement learning Chao Xing slides video(part 1) video(part 2) an old but good review state-of-the-art course
2016/08/02 Dong Wang Optimization Caixia; slides Convex optimization I Convex optimization II