Advanced Topics in Machine Learning
This web page provides information on the course Advanced Topics in Machine Learning (summer term 2012). The course deals with selected topics of Machine Learning, including:
- Support Vector Machines
- Semi-Supervised Learning (semi-supervised classification and clustering)
- Dealing with massive datasets
Prerequisite for attending this course is a basic knowledge of computer science, especially in Machine Learning. Programming skills are an advantage concerning the pratical exercises.
Course Schedule and Room Assignments
Title | Time | Start | Room |
Lecture | Thursday 5:00pm - 7:00pm | 12.04.2012 | G29-K058 |
Exercises | Monday 11:00am - 1:00pm | 16.04.2012 | G22A-122 |
Further information on the lecture and the exercise can be found in the LSF portal.
Course Staff
If you have any questions concerning the lectures or assignments please contact (preferably by email):
Exercise Classes
The exercise classes have two objectives. First, regular assignments concerning the theory taught in the lecture will be given (about one week in advance). These have to be prepared by the students and are then discussed during class. Secondly, the lecture will be accompanied by a software project. Its goal is to practice the implementation of machine learning techniques into a larger system. This will be done as a joint group work. The development will partly be done during the exercise classes. However, further development outside the class might be necessary to complete the project. We expect active involvement of all students, both in the project and the theoretical assignments.
Requirements for Class Fulfillment
At the end of the course, there will be an oral exam. As a prerequisite, we expect active involvement both during the exercise and in the software project.
Materials
We will provide lecture slides, assignment sheets, and further material during the course.
Lecture Slides
- Course Information
- Fundamentals
- Computational Learning Theory
- Support Vector Machines
- Semi-Supervised Learning
- Constrained Clustering
- Markov Models
- Massive Datasets
Exercise Material
- Assignment Sheet 1 (Slides)
- Assignment Sheet 2
- No Assignments on 30th April, instead:
- Short Talk on the Curse of Dimensionality
- Discussion on the Software Project
- Assignment Sheet 3
- Assignment Sheet 4
- Assignment Sheet 5
- Assignment Sheet 6
- Assignment Sheet 7
- Assignment Sheet 8
- Assignment Sheet 9
- Assignment Sheet 10
- Assignment Sheet 11 (due by 09th of July)
Further Material
- Programming Environment (last update 11th of June)