Spectral operators of matrices

نویسندگان

  • Chao Ding
  • Defeng Sun
  • Jie Sun
  • Kim-Chuan Toh
چکیده

The class of matrix optimization problems (MOPs) has been recognized in recent years to be a powerful tool to model many important applications involving structured low rank matrices within and beyond the optimization community. This trend can be credited to some extent to the exciting developments in emerging fields such as compressed sensing. The Löwner operator, which generates a matrix valued function via applying a single-variable function to each of the singular values of a matrix, has played an important role for a long time in solving matrix optimization problems.However, the classical theory developed for theLöwner operator has become inadequate in these recent applications. The main objective of this paper is to provide necessary theoretical foundations from the perspectives of designing efficient numerical methods for solving MOPs. We achieve this goal by introducing and conducting a thorough study on a new class of matrix valued functions, coined as spectral operB Defeng Sun [email protected] Chao Ding [email protected] Jie Sun [email protected] Kim-Chuan Toh [email protected] 1 Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, People’s Republic of China 2 Department of Mathematics and Risk Management Institute, National University of Singapore, Singapore, Singapore 3 Department of Mathematics and Statistics, Curtin University, Bentley, Australia 4 Department of Mathematics, National University of Singapore, Singapore, Singapore

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عنوان ژورنال:
  • Math. Program.

دوره 168  شماره 

صفحات  -

تاریخ انتشار 2018