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Seminar Machine Learning
Machine Learning Seminar WS 2010/2011
Machine Learning seminar - WS 2010/2011
Content:
In this seminar, we will present and discuss selected topics related to machine learning. Machine learning is aimed at devising algorithms that can learn from examples to tackle certain tasks. Generally, machine learning techniques can be associated with one of the following two categories – supervised and unsupervised learning.
Tutors:
Time:
Place:
Schedule:
Preliminary discussion, Thursday 21.10.2010, 12.00-13.00, Seminar room at INB
Seminar Schedule:
| Student | Topic | Date | Advisor |
|---|---|---|---|
| Florian Hartmann |
Nearest-Neighbor Based Image Classification |
03.02.2010 |
laura |
| Tobias Meyer |
High-Dimensional Data Analysis: The Curses and Blessings of Dimensionality |
27.01.2010 | tkaester |
| Marc Hallmann |
Mixtures of Gaussians and the EM Algorithm |
10.02.2010 | laura |
| Michael Brehler |
PCA and ICA |
03.02.2010 | tkaester |
| Georg Zeplin |
Sparse Coding |
10.02.2010 | laura |
Certificate:
Obtaining a seminar certificate requires to give a presentation and write a term paper. The paper should be limited by 10 pages and the ACM style should be used. The corresponding templates are available for LaTex and MS Word. Please submit the paper in PDF until 15.02.2010.Remarks:
We expect every presenter to show their slides to us at least one week before the actual presentation date (personally, not only by email!!!). If questions arise during your preparation, do not hesitate to make an appointment with us. However, please prepare yourself sufficiently, so that we can resolve all questions in one or two sessions.
Topics
Please download the following PDF file: SemMachineLearningPDF
