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Low Rank Approximation

MA5328A1.3 Mathematics Modules on Special Topics3 ECTSEnglishEinmaligDepartment Mathematics
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You will learn methods for low-rank approximation of matrices and tensors, including singular value decomposition and various tensor factorizations. In the end you will be able to assess which approximation is suitable for a given application and apply and implement it for data compression or analysis.

What you will be able to do

  • Analyze applications
  • Select suitable low-rank approximations
  • Develop and apply low-rank approximations (e.g., compression, data analysis)

What the module consists of

  • VorlesungTransmission of the theoretical foundations and methods

Teaching method

  • Vorlesungfor the introduction and explanation of concepts and algorithms
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Official page in TUMonline · Details are not binding.