“2016 Summer Seminar for Machine learning”版本间的差异
来自cslt Wiki
| 第24行： | 第24行： | ||
| 2016/07/25 ||Dong Wang || Unsupervised learning || ||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt9.%20Unsupervised%20Learning.pptx slides] [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] | | 2016/07/25 ||Dong Wang || Unsupervised learning || ||[http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt9.%20Unsupervised%20Learning.pptx slides] [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://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process] | + | | 2016/07/26 ||Dong Wang || Non parametric models ||Maoning Wang; || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process] [http://stat.columbia.edu/~porbanz/npb-tutorial.html Resource for non-parametric Bayesian] |
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| 2016/07/27 ||Dong Wang || Reinforcement learning || || | | 2016/07/27 ||Dong Wang || Reinforcement learning || || | ||
2016年7月26日 (二) 01:06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 | 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 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; | Gaussian process Resource for non-parametric Bayesian |
| 2016/07/27 | Dong Wang | Reinforcement learning | ||
| 2016/07/28 | Maoning Wang | Evolutionary learning | Maoning Wang; | |
| 2016/07/29 | Dong Wang | Optimization | Caixia; | Convex optimization I Convex optimization II |
