Multimedia Computing and Computer Vision Lab

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WS 09/10: Maschinelles Lernen I

From Multimedia Computing Lab - University of Augsburg


Registration is open! LectureReg

Recent Exercise:
Recent Slides:

Overview

Instructors: Dr. Eva Hörster
Time Lecture: Tue, 14:00 - 15:30, Room: 1055 N
Time Exercise: Tue, 15:45 - 17:15, Room: 1055 N
Credits: 2 + 2 SWS, Schein, yes, LP 5
Exam: Feburary 18th, 10:00-11:30 AM, room 1058N
Multimedia Teilbereiche: Multimedia Methoden, Multimedia Anwendungen, Systemnahe Grundlagen von Multimedia

Exercise and Exam

  • There will be an exercise sheet every week
  • Solutions will be discussed during exercises on Tuesdays (no handing-in or revision of written solutions)
  • No admission requirements for the exam
  • Exam date will be Feburary 18th, 10:00-11:30 AM, room 1058N
  • The results of the final exam can be looked up in LectureReg.
  • You may inspect your final exams on Thursday, March 4th, between 10:00 a.m. and 12 p.m. in room 1020N.

Important Comments

  • The results of the final exam can now be looked up in LectureReg.
  • You may inspect your final exams on Thursday, March 4th, between 10:00 a.m. and 12 p.m. in room 1020N.
  • The exam will be written on Feburary 18th, 10:00-11:30 AM in room 1058N.
  • There will be no lecture and exercise on Febuary 2nd.
  • On Feburary 9th, we will first discuss the last exercise sheet and then you will have the opportunity to ask questions.
  • The lecture has been moved to room 1055 N
  • Vorlesung wird auf Deutsch gehalten (trotz der englischsprachigen Folien und Literatur)
  • All reading notes are relevant for the exams independent on how thoroughly they have been discussed during the lecture. Thus read and study them carefully.

Literature

  1. Christopher M. Bishop. Pattern Recognition and Machine Learning. Springer Verlag. (http://research.microsoft.com/en-us/um/people/cmbishop/prml/)


Material

Date Content Slides Exercise
20.10.2009 Organization PDF
27.10.2009 Introduction to Machine Learning PDF PDF
03.11.2009 Probability Distributions PDF PDF
10.11.2009 Probability Distributions PDF PDF
17.11.2009 Linear Models for Regression PDF PDF
24.11.2009 Linear Models for Regression PDF PDF MatrixIDs GaussIDs
01.12.2009 Linear Models for Classification PDF PDF
08.12.2009 Neural Networks PDF PDF
15.12.2009 Neural Networks PDF PDF
22.12.2009 Neural Networks PDF Research papers:(http://vasc.ri.cmu.edu/NNFaceDetector/)
12.01.2010 Kernel Methods PDF PDF
19.01.2010 Support Vector Machines PDF PDF
26.01.2010 Combining Models PDF PDF