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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)

SS 2016, TU München

Lecture

Location: Room 02.09.023
Date: Friday, starting at 22nd April
Time: 9.15
Lecturer: PD Dr. habil. Rudolph Triebel
ECTS: 4
SWS: 3

Tutorial

Location: Room 02.09.023
Date: every second Friday, starting at 29th April
Time: 15.00
Lecturer: John Chiotellis


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
- Boosting
- Neural Networks and Deep Learning
- Kernel Methods
- Gaussian Processes
- Evaluation and Model Selection
- Sampling Methods
- Clustering

Lecture Slides
Exercises
Exam Preparation

To prepare for the exam you can be helped by studying the questions here.

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85748 Garching info@vision.in.tum.de

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