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TUM Department of Informatics
Technical University of Munich

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Machine Learning for Robotics and Computer Vision (IN3200) (2h + 1h, 4ECTS)

WS 2016, TU München

Lecture

Location: Room 02.13.010
Date: Friday
Time: 10.15 - 12.00
Lecturer: PD Dr. habil. Rudolph Triebel
ECTS: 4
SWS: 3

Tutorial

Location: Room 02.09.023
Date: every second Friday starting from 28.10.2016
Time: 14.00 - 16.00
Lecturer: John Chiotellis

There will be no more tutorials after January, 27th.

Exam Information

Location: 101, Interims Hörsaal 1 (5620.01.101)
Date: Friday, February 24th
Time: 16.00 - 17.30

No assisting material is allowed, like calculators, formula sheets, etc.
Please note that there will be no repeat exam, since the lecture is offered in every semester.

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.

Tentative Schedule:
- Introduction
- Regression
- Probabilistic Graphical Models
- Distance Metric Learning
- Boosting
- Neural Networks and Deep Learning
- Kernel Methods
- Gaussian Processes
- Evaluation and Model Selection
- Sampling Methods
- Clustering

Lecture Slides
Exercises

Rechte Seite

Informatik IX
Chair of Computer Vision & Artificial Intelligence

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

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