-

 

 

 




Optimization Online





 

Positive semidefinite matrix approximation with a trace constraint

Kouhei Harada(harada***at***msi.co.jp)

Abstract: We propose an efficient algorithm to solve positive a semidefinite matrix approximation problem with a trace constraint. Without constraints, it is well known that positive semidefinite matrix approximation problem can be easily solved by one-time eigendecomposition of a symmetric matrix. In this paper, we confirmed that one-time eigendecomposition is also sufficient even if a trace constraint is included. Although an additional binary search is necessary, it is not computationally expensive.

Keywords: positive semidefinite matrix approximation, nearest matrix, trace constraint, projection onto a simplex, simplex constraint

Category 1: Linear, Cone and Semidefinite Programming (Semi-definite Programming )

Category 2: Convex and Nonsmooth Optimization (Convex Optimization )

Citation:

Download: [PDF]

Entry Submitted: 08/08/2018
Entry Accepted: 08/08/2018
Entry Last Modified: 08/08/2018

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Optimization Society