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| * '''Learning Theory''' * '''Multi-Task Learning''' * '''Robust Parameter Estimation''' |
Block-Seminar "Classical Topics in Machine Learning"
Termine und Informationen
Erster Termin für Themenvergabe |
Montag, 03.11.2014, 10:00 in MAR 4.033 |
Verantwortlich |
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Dozent: |
Dr. Wojciech Samek (wojciech.samek@hhi.fraunhofer.de, Raum MAR 4.060) |
Sprache |
Englisch |
Anrechenbarkeit |
Wahlpflicht LV im Modul Maschinelles Lernen I (Informatik M.Sc.) |
ISIS |
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This seminar takes a closer look at classical topics in machine learning.
Students will read, understand, evaluate and present selected research papers on machine learning methods in different applications settings. At the end of the semester, each student will present his/her topic in a 25-30 min talk (+ questions) in English.
The topics of the seminar are:
Boosting
Neural Networks
Feature Selection
Optimization Algorithms
Independent Component Analysis
Structured Prediction
Kernel Methods
Support Vector Machines
Gaussian Processes
Learning Theory
Multi-Task Learning
Robust Parameter Estimation