Techn. Fakultät Willkommen am Institut für Informatik FAU-Logo


General Information

The first date for the lecture is 

Wednesday, October 19, 2011 in room 00.153, 12:15.

The exercises will start October 24, more information is given in the first lecture.


The lecture will discuss the following topics: 

  • Classification and Simple Patterns
  • Bayesian Classifier
  • Logistic Regression
  • Gaussian Classifiers and Naive Bayes
  • Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA)
  • Linear Regression, Ridge Regression, Lasso
  • Rosenblatt's Perceptron and Multi-Layer Perceptrons (MLP)
  • Support Vector Machines (SVM), Laplacian SVM
  • Kernels
  • Gaussian Mixture Models (GMM) and the Expectation Maximization (EM) Algorithm
  • Independent Component Analysis (ICA)
  • Model Assessment and Selection
  • AdaBoost

The methods and procedures that are presented in this lecture are illustrated in the exercise courses. The tutorials put emphasis on the practical realization of these methods. 


The slides of the lecture are available here.

It is absolutely recommended to attend the lectures in order to make personal notes. In addition, covered topics should be completed with personal research in the recommended technical literature and publications that will be announced in the lecture.


The web page of the exercise courses is here.

It is absolutely recommended to attend the exercise courses and to do the assigned homework in order to get a deeper understanding of the topics discussed in the lecture.

Video Recordings

The topics of this lecture are similar to the ones of the lecture 'Musteranalyse/Pattern Analysis' given by Prof. Hornegger in the summer term 2009. However, new chapters (e.g. Laplacian SVM, ICA, Model Assessment, AdaBoost) have been added, whereas others (e.g. HMM) are not discussed in this lecture any more.

The videos are available here.