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||'''Verantwortlich'''|| [[http://www.ml.tu-berlin.de/menue/members/klaus-robert_mueller/|Prof. Dr. Klaus-Robert Müller]] || ||'''Verantwortlich'''|| Prof. Dr. Klaus-Robert Müller ||

Block-Seminar "Classical Topics in Machine Learning"

Termine und Informationen

Erster Termin für Themenvergabe

TBD

Termin für Präsentation

TBD

Verantwortlich

Prof. Dr. Klaus-Robert Müller

Dozenten:

Stefan Chmiela chmidhkg@mailbox.tu-berlin.de

Kristof Schütt kristof.schuett@tu-berlin.de

Sprache

Englisch

Anrechenbarkeit

Wahlpflicht LV im Modul Maschinelles Lernen I (Informatik M.Sc.)

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 20 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

IDA Wiki: Main/WS17_ClassicalTopics (last edited 2017-11-27 12:55:31 by KristofSchuett)