youtube - UniHeidelberg: Pattern Recognition
Published on Nov 22, 2012
The Pattern Recognition Class 2012 by Prof. Fred Hamprecht.
It took place at the HCI / University of Heidelberg during the summer term of 2012.
Website: h-ttp://hci.iwr.uni-heidelberg.de/MIP/Teaching/pr/
Playlist with all videos: h-ttp://goo.gl/gmOI6
Contents of this recording:
00:06:09 - Laser Welding Monitoring
00:07:00 - Imaging Mass Spectrometry -
00:07:24 - Connectomics
00:13:08 - Cluster Analysis
Syllabus:
1. Introduction
1.1 Applications of Pattern Recognition
1.2 k-Nearest Neighbors Classification
1.3 Probability Theory
1.4 Statistical Decision Theory
2. Correlation Measures, Gaussian Models
2.1 Pearson Correlation
2.2 Alternative Correlation Measures
2.3 Gaussian Graphical Models
2.4 Discriminant Analysis
3. Dimensionality Reduction
3.1 Regularized LDA/QDA
3.2 Principal Component Analysis (PCA)
3.3 Bilinear Decompositions
4. Neural Networks
4.1 History of Neural Networks
4.2 Perceptrons
4.3 Multilayer Perceptrons
4.4 The Projection Trick
4.5 Radial Basis Function Networks
5. Support Vector Machines
5.1 Loss Functions
5.2 Linear Soft-Margin SVM
5.3 Nonlinear SVM
6. Kernels, Random Forest
6.1 Kernels
6.2 One-Class SVM
6.3 Random Forest
6.4 Random Forest Feature Importance
7. Regression
7.1 Least-Squares Regression
7.2 Optimum Experimental Design
7.3 Case Study: Functional MRI
7.4 Case Study: Computer Tomography
7.5 Regularized Regression
8. Gaussian Processes
8.1 Gaussian Process Regression
8.2 GP Regression: Interpretation
8.3 Gaussian Stochastic Processes
8.4 Covariance Function
9. Unsupervised Learning
9.1 Kernel Density Estimation
9.2 Cluster Analysis
9.3 Expectation Maximization
9.4 Gaussian Mixture Models
10. Directed Graphical Models
10.1 Bayesian Networks
10.2 Variable Elimination
10.3 Message Passing
10.4 State Space Models
11. Optimization
11.1 The Lagrangian Method
11.2 Constraint Qualifications
11.3 Linear Programming
11.4 The Simplex Algorithm
12. Structured Lear
教程列表:
Introduction _ Pattern Recognition 1-1
Introduction _ Pattern Recognition1.2
Introduction _ Pattern Recognition Class 1.3
Introduction _ Pattern Recognition Class 1.4
Introduction _ Pattern Recognition Class 2.1
Introduction _ Pattern Recognition Class 2.2
海德堡大学:模式识别 2.4 高斯图形模型和相关性判定
海德堡大学:模式识别 3.1
海德堡大学:模式识别 2.3 高斯图形模型和相关性判定
海德堡大学:模式识别3.2
海德堡大学:模式识别4.3
海德堡大学:模式识别4.2
海德堡大学:模式识别4.1