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Techn. Fakultät Willkommen am Institut für Informatik FAU-Logo

Lecture

Organization

The lecture takes places:

  • Monday, 08:30 - 10:00am, H16
  • Tuesday, 08:15 - 09:45am, H16

 

 

NEWS

No lecture on monday, 20.04.2015.

Outline

1. Introduction

2. Clustering

   2.1 Introduction

   2.2 Distance Measures

   2.3 Hard Clustering

   2.4 Soft Clustering

   2.5 Variants of Soft Clustering

 3. Density Estimation

   3.1 Introduction

   3.2 Parametric Density Estimation

   3.3 Non-parametric Density Estimation

   3.4 Convolution with Parzen Kernel

   3.5 Parzen Window Width Estimation

   3.6 Histogram Layout by Regression Trees

4. Mean Shift Algorithm

   4.1 Theory of Mean Shift Algorithm

5. Manifold Learning

   5.1 Curse of Dimensionality

   5.2 Principal Component Analysis (PCA)

   5.3 Multidimensional Scaling (MDS)

   5.4 Sammon Transform

   5.5 Local Linear Embedding (LLE)

   5.6 Isometric Feature Mapping (ISOMAP)

   5.7 Laplacian Eigenmaps

  

...to be continued

Additional Material

Title
Topic
Sheet
Dorin Comaniciu and Peter Meer
Mean Shift: A Robust Approach Towards Feature Space Analysis

IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 24, Issue 5, Pages 603 - 619, May 2002
Mean shiftOpens external link in new windowPDF
Mean shift algorithm

Mean

shift

Initiates file downloadPDF

Sam T. Roweis and Lawrence K. Saul
Nonlinear Dimensionality Reduction by Locally Linear Embedding

Science, Volume 290, Number 5500, Pages 2323--2326, 2000

Dimensionality ReductionInitiates file downloadPDF
Korbinian Riedhammer
Large Vocabulary Continuous Speech Recognition
Hidden Markov
Models
Initiates file downloadPDF

Joachim Hornegger
Markov Random Fields

Markov
Random Fields
Initiates file downloadPDF

Rita Osadchy
Manifold Learning

Manifold LearningOpens external link in new windowPDF
Yaron Ukrainitz, Bernard Sarel
Mean Shift - Theory and Applications
Mean ShiftOpens external link in new windowPPT
Jeff A. Bilmes
A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models
Hidden Markov ModelsInitiates file downloadPDF
Lawrence R. Rabiner
A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition
Hidden Markov ModelsInitiates file downloadPDF