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

来自cslt Wiki
跳转至: 导航搜索
第16行: 第16行:
 
| 2016/07/12  ||Dong Wang  || Deep learning (2)|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
 
| 2016/07/12  ||Dong Wang  || Deep learning (2)|| [http://wangd.cslt.org/talks/seminar/2016-sum-ml/chpt5.%20Deep%20learning-2.pptx slides] [http://www.icassp2016.org/SP16_PlenaryDeng_Slides.pdf Li Deng's ICASSP16 keynote]
 
|-
 
|-
| 2016/07/13    ||Caixia Wang  || Kernel methods || [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]
 
|-
 
|-
 
|2016/07/    ||Dong Wang  || Unsupervised learning ||  
 
|2016/07/    ||Dong Wang  || Unsupervised learning ||  

2016年7月13日 (三) 06:11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/ Dong Wang Unsupervised learning
2016/07/ Dong Wang Probabilistic learning theory
2016/07/ Yang Feng Graphical model: Bayesian approach
2016/07/ Yang Feng Graphical model: Random field
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