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Home Teaching Summer Semester 2017 Machine Learning for Robotics and Computer Vision (IN3200) (2h + 1h, 4ECTS)

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

SS 2017, TU München

Lecture

Location: Room 01.11.018
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 May 5th
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
Last edited 13.03.2017 16:02 by Ioannis Chiotellis