Neural Networks and Learning Theory - Sommersemester 2019

LectureTue11:30 - 13:00HG 0.19Prof. Dr. Klaus Meer
LectureWe09:15 - 10:45HG 2.44Prof. Dr. Klaus Meer
ExerciseFr11:30 - 13:00HG 0.17M. Sc. Ameen Naif

Course information

  • Enrollment: 
    1. electronically for the module
    2. You have to register yourself in Moodle using your BTU account.
        There is no password required, registration can be done immediately.
  • first lecture: 2 April 2019. Here, we shall also discuss potential changes of the lecturing hours.
  • first exercise: 5 April 2019
  • Final exam: The final exam will an oral one. More details will be given during the course.

Additional Literature

  • E. Alpaydin: Maschinelles Lernen, Oldenbourg Verlag München, 2008
  • M. Anthony, N.Biggs: Computational Learning Theory, Cambridge University Press 1997
  • N. Christiani, J. Shawe-Taylor: An Introduction to Support Vector Machines and kernel-based Learning Methods, Cambridge Univ. Press,  2003
  • A.C.C Coolen, R. Kühn, P. Sollich: Theory of Neural Information Processing Systems, Oxford University Press 2005
  • P. Fischer: Algorithmisches Lernen, Teubner 1999
  • P. Flach: Machine Learning: The Art and Science of Algorithms that Make Sense of Data, Cambridge University Press 2012
  • F. M. Ham, I. Kostanic: Principles of Neurocomputing for Science & Engineering, McGraw Hill 2001
  • S. Haykin: Neural Networks, Prentice Hall, 1999
  • R. Rojas: Theorie der neuronalen Netze, Springer 1996
  • S. Shalev-Shwartz, S. Ben-David: Understanding Machine Learning, Cambridge University Press 2014.

Online-Sammlung zahlreicher Artikel:PASCAL 2

Zeitschriften (Auswahl):

Exercise sheets

sheet 1
online since: 09.04.2019
sheet 2
online since: 25.04.2019
sheet 3
online since:17.05.2019
sheet 4
online since:13.06.2019
sheet 5
online since: 05.07.2019
sheet 6
online since: