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Technical University of Munich

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Machine Learning for Robotics and Computer Vision

SS 2013, TU München

Lecture

Location: Room 02.09.023
Date: Friday, starting at 26th April
Time: 9.15
Lecturer: Dr. Rudolph Triebel
ECTS: TBC
SWS: 3

Tutorial

Location: Room 02.09.023
Date: Friday, 3rd May, every other week
Time: 14.15
Lecturer: Jan Stühmer

The course will be held in English.

Contents

In this lecture, the students will be introduced into the most frequently used machine learning methods in computer vision and robotics applications. The major aim of the lecture is to obtain a broad overview of existing methods, and to understand their motivations and main ideas in the context of computer vision and pattern recognition. Also, in addition to the standard methods, the lecture will also cover some recent topics such as CRFs, Random Forests, and IVMs.

Schedule:
- Introduction
- Regression
- Probabilistic Graphical Models
- Boosting
- Kernel Methods
- Gaussian Processes
- Evaluation and Model Selection
- Sampling Methods
- Clustering

Lecture Slides
Exercises

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Informatik IX
Chair of Computer Vision & Artificial Intelligence

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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