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Additional Courses

These courses are for some of our research directions (and hence also for topics for Bachelor and Master Theses) quite useful.

Random Matrices and Matrix Completion
Special course 26.09. - 30.09.2016
Selected topics from the following area:
  • Introduction to randomness: concentration of measure, Lemma of Johnson and Lindenstrauss
  • Low-rank matrix recovery: Rank r-Null space property, Rank r-Restricted isometry property, Gaussian information map
  • Random matrices: Matrix norms, Golden-Thompson inequality, Non-commutative Bernstein inequality, Lieb's theorem
  • Matrix Completion: Recovery of a low-rank matrix from few observed entries
Summer 2016
Room
Time
Lecture
MA 313
Daily: 10-12 & 14-16
Further information available: Webpage, course catalog and ISIS
Compressive Sensing and Inverse Problems in Signal Processing
Course in the Area of Compressed Sensing
This course is regularly offered in Electrical Engineering in the Winter Term by Dr. Peter Jung and provides an excellent introduction into various topics of Compressed Sensing.
Convex Geometry I/II
Courses in the Area of Geometric Functional Analysis
These courses are regularly offered in Mathematics by Prof. Dr. Martin Henk and provide an excellent introduction into diverse topics in the realm of Geometric Functional Analysis. They are hence also very useful for the area of Compressed Sensing.
Maschine Learning I/II
Courses in the Area of Data Science
These courses are regularly offered in Computer Science by Prof. Dr. Klaus-Robert Müller and provide an excellent introduction into diverse topics in data science.
Nonlinear Optimization
Course in the Area of Data Science
This course is regularly offered in Mathematics, e.g., by Prof. Dr. Fredi Tröltzsch and provides an excellent introduction into diverse topics in nonlinear optimization, also convex optimization. It is hence also very useful for the compressed sensing, or more generally the area of data science.
Numerical Analysis of Partial Differential Equations
Course in the Area of Partial Differential Equations
This course is regularly offered in Mathematics, e.g., by Prof. Dr. Reinhold Schneider and provides an excellent introduction into numerical aspects of partial differential equations, also covering approaches which use systems from applied harmonic analysis.

 

 

 

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