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Seminar Learning

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Seminar Learning



Data, data, data...

One huge, but exciting challenge of the 21th century posed to

mathematicians is the deluge of data, caused by

  • Telecommunication
  • Medicine
  • Genomics
  • Social Networks
  • Astronomy
  • ...

Various types of data

  • 1D functions: Signals
  • 2D functions: Images
  • 3D functions: Videos
  • >= 1000D function: High-Dimensional Data
  • Functions on manifolds and manifold-valued functions
  • Functions on graphs

Key approaches

  • Applied Harmonic Analysis – Finding suitable structured representations!
  • Deep Neural Networks – Learning representations, in particular, for classification
  • Compressed Sensing – Acquiring only the compressed part of data
    This can be used to solve linear inverse problems in general.
  • Machine Learning – Find patterns in data
  • Spectral Theory (on Graphs) – Analyze the spectrum of data


The seminar will take place in winter term 2017/2018 on Thursdays from 3.30 pm to 5pm, the room will be announced.

Please apply before September 30, 2017 via E-Mail to Ronny Bergmann (Subject: Seminar Learning). The number of participants is limited to at most 12 students.

The image of the painting “Composition 8” by Wassliy Kandinsky is public domain and available in the wikimedia.