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This material is copyrighted (c) 2006-2013 by Joachim Hornegger, Dieter Hahn, and Stefan Steidl, Friedrich-Alexander University of Erlangen-Nuremberg, Germany. Use without prior written permission of the authors is not permitted!

 

 

These slides are part of a presentation. The presentation is not complete without the verbal explanations given during the lecture.

 

We will update the slides during the semester as needed in order to improve the quality of our slides.
Please make sure that you have the latest version of our slides in preparation for the exam.

 

 

Chapter Lecture

Slides

Date SlidesScreen
Print (A5)Print (A6) Update
1 Introduction 15.10.2013 1-1 - 1-35 pdfpdfpdf15.10.2013
2 Bayesian classifier 16.10.2013 2-1 - 2-16 pdfpdfpdf15.10.2013
3 Logistic Regression I 22.10.2013 3-1 - 3-33 pdfpdfpdf22.10.2013
4 Logistic Regression II 23.10.2013 4-1 - 4-19 pdfpdfpdf23.10.2013
5 Naive Bayes 29.10.2013 5-1 - 5-19 pdfpdfpdf20.01.2014
6 Linear Discriminant Analysis I 29.10.2013 6-1 - 6-21 pdfpdfpdf23.10.2013
7 Linear Discriminant Analysis II 30.10.2013 7-1 - 7-6 pdfpdfpdf07.11.2013
05.11.2013 7-7 - 7-30
06.11.2013 7-31 - 7-37
8 Norms and Norm Dependent Linear Regression 06.11.2013 8-1 - 8-7 pdfpdfpdf12.11.2013
12.11.2013 8-8 - 8-36
9 Rosenblatt's Perceptron 12.11.2013 9-1 - 9-8 pdfpdfpdf14.11.2013
13.11.2013 9-9 - 9-18
10 Multi-Layer Perceptrons 13.11.2013 10-1 - 10-11 pdfpdfpdf13.11.2013
19.11.2013 10-12 - 10-17
11 Optimization 19.11.2013 11-1 - 11-10 pdfpdfpdf14.11.2013
20.11.2013 11-11 - 11-26
26.11.2013 11-27 - 11-35
12 Support Vector Machines I 26.11.2013 12-1 - 12-11 pdfpdfpdf18.11.2013
27.11.2013 12-12 - 12-15
13 Duality in Optimization 27.11.2013 13-1 - 13-7 pdfpdfpdf29.11.2013
03.12.2013 13-8 - 13-20
14 Support Vector Machines II 03.12.2013 14-1 - 14-8 pdfpdfpdf04.12.2013
04.12.2013 14-9 - 14-19
15 Kernels 10.12.2013 15-1 - 15-20 pdfpdfpdf20.12.2013
11.12.2013 15-21 - 15-28
17.12.2013 15-29 - 15-34
16 Laplacian Support Vector Machines 17.12.2013 16-1 - 16-18 pdfpdfpdf16.12.2013
The Big Picture 18.12.2013
17 The Expectation Maximization Algorithm 07.01.2014 17-1 - 17-11 pdfpdfpdf20.12.2013
08.01.2014 17-12 - 17-29
14.01.2014 17-30 - 17-41
18 Adaptive Segmentation of MRI Data 15.01.2014 18-1 - 18-14 pdfpdfpdf21.01.2014
21.01.2014 18-15 -18-25
19 Independent Component Analysis 21.01.2014 19-1 - 19-26 pdfpdfpdf21.01.2014
22.01.2014 19-27 - 19-47
28.01.2014 19-48 -
20 Model Assessment new 28.01.2014 20-1 - 20-23 pdfpdfpdf29.01.2014
29.01.2014 20-24 - 20-38
Evalution Results 29.01.2014
21 AdaBoost 04.02.2014 21-1 - 21-41 pdfpdfpdf04.02.2014
05.02.2014 canceled

 

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