“2016 Summer Seminar for Machine learning”版本间的差异
来自cslt Wiki
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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 || [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 || | ||
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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 || | ||
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| 2016/07/ ||Dong Wang || No parametric models || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process] | | 2016/07/ ||Dong Wang || No parametric models || [http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf Gaussian process] | ||
2016年7月14日 (四) 02:28的版本
- Location: FIT-1-304
| Date | Speaker | Title | 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 | slides NG's lecture 1 NG's lecture 2 |
| 2016/07/08 | Dong Wang | Neural networks | slides |
| 2016/07/11 | Dong Wang | Deep learning (1) | slides NIPS 2015 tutorial |
| 2016/07/12 | Dong Wang | Deep learning (2) | slides Li Deng's ICASSP16 keynote |
| 2016/07/13 | Caixia Wang | Kernel methods | slides Kernel method book pattern recognition 6-7 |
| 2016/07/ | Yang Feng | Graphical model: Bayesian approach | |
| 2016/07/ | Yang Feng | Graphical model: Random field | |
| 2016/07/ | Dong Wang | Unsupervised learning | |
| 2016/07/ | Dong Wang | No 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 |
