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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'''
 * '''ICA'''
 * '''Structured Prediction'''
 * '''Kernel Methods'''
 * '''Support Vector Machines'''
 * '''Gaussian Processes'''

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

Prof. Dr. Klaus-Robert Müller

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

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

  • ICA

  • Structured Prediction

  • Kernel Methods

  • Support Vector Machines

  • Gaussian Processes

IDA Wiki: Main/WS14_SeminarClassicalTopicsInML (last edited 2014-11-27 16:12:31 by WojciechWojcikiewicz)