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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 2017, TU München

Lecture

Location: Room MW HS0250
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 Tuesday starting from May 16th
Time: 14.00 - 16.00
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
- Metric Learning
- 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. Note that these are questions from oral exams of previous semesters and do not necessarily cover all topics covered in the current semester.

Exam Information
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.

Date: August 18th
Time: 8:30 - 10:00
Location: 102, Interims Hörsaal 2 (5620.01.102)

Exam Review
Please bring your TUM ID card with you.

Date: September 15th
Time: 10:00 - 11:00
Location: Room 02.09.023

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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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