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||'''Erster Termin für Themenvergabe'''|| TBD ||
||'''Termin für Präsentation'''|| TBD ||
||'''Verantwortlich'''|| Prof. Dr. Klaus-Robert Müller ||
|| '''Kickoff Meeting''' || Monday 27 November 2017 from 8am to 9am in room H 107 ||
||'''Presentation Days'''|| Thursday-Friday, 22-23 February 2018 from 9am to 7pm in room MAR 4.065 ||

Block-Seminar "Classical Topics in Machine Learning"

Termine und Informationen

Kickoff Meeting

Monday 27 November 2017 from 8am to 9am in room H 107

Presentation Days

Thursday-Friday, 22-23 February 2018 from 9am to 7pm in room MAR 4.065

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)