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Home Teaching Winter Semester 2013/14 Machine Learning for Robotics and Computer Vision

Machine Learning for Robotics and Computer Vision

WS 2013/2014, TU München

Lecture

Location: Room 02.09.023
Date: Friday, starting at 25th October
Time: 9.15
Lecturer: Dr. Rudolph Triebel
ECTS: 4
SWS: 3

Tutorial

Location: Room 02.09.023
Date: Friday, starting at 8th November
Time: 14.15
Lecturer: Matthias Vestner

The next tutorial will be on Friday, 24th January


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
Homework
Videos

Note that the video titles on YouTube start with index 1, while the lectures start with 2, so the video index is always 1 lower than the number of the lecture.

Last edited 20.02.2014 14:38 by Matthias Vestner