Kronecker Product Approximation of Operators in Spectral Norm via Alternating SDP


Event details

Date 09.02.2023
Hour 11:0012:00
Speaker Prof. André Uschmajew - University of Augsburg
Category Conferences - Seminars
Event Language English
Computational Mathematics Seminar
: The decomposition or approximation of a linear operator on a matrix space as a sum of Kronecker products plays an important role in matrix equations and low-rank modeling. The approximation problem in Frobenius norm admits a well-known solution via the singular value decomposition.
However, the approximation problem in spectral norm, which is more natural for linear operators, is much more challenging. In particular, the Frobenius norm solution can be far from optimal in spectral norm. We describe an alternating optimization method based on semidefinite programming to obtain high-quality approximations in spectral norm, and we present computational experiments to illustrate the advantages of our approach. Based on joint work with Mareike Dressler and Venkat Chandrasekaran.

Practical information

  • General public
  • Free


  • Prof. Daniel Kessner


  • Prof. Daniel Kressner
    Samantha Bettschen



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