Solving some large scale semidefinite programs via the conjugate residual method

SIAM Journal on Optimization

Volumn 12, Issue 3, 2002, Pages 669-691

  Toh, Kim Chuan ^a   Kojima, Masakazu ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Deflated conjugate gradient method; Inexact search directions; Interior point methods; Large scale semidefinite programming; Preconditioned conjugate residual method

Indexed keywords

EID: 0036361611     PISSN: 10526234     EISSN: None     Source Type: Journal    
DOI: 10.1137/S1052623400376378     Document Type: Article

References (24)

1. Complementarity and nondegeneracy in semidefinite programming
2. A library of semidefinite programming test problems. Interior point methods
3. Solving large-scale sparse semidefinite programs for combinatorial optimization
4. GMRES on (nearly) singular systems
5. From potential theory to matrix iterations in six steps
6. Exploiting sparsity in primal-dual interior-point methods for semidefinite programming
7. Exploiting sparsity in semidefinite programming via matrix completion I: General framework
8. Estimating the attainable accuracy of recursively computed residual methods
9. A spectral bundle method with bounds
10. An interior-point method for semidefinite programming
11. Interior-point methods for the monotone semidefinite linear complementarity problem in symmetric matrices
12. Search directions in the SDP and the monotone SDLCP: Generalization and inexact computation
13. Primal-dual path-following algorithms for semidefinite programming
14. Using the conjugate gradient method in interior-points methods for semidefinite programs
15. Preconditioned conjugate gradient methods for large scale and dense linear systems in semidefinite programming
16. A deflated version of the conjugate gradient algorithm
17. On the real convergence rate of the conjugate gradient method
18. On the Nesterov-Todd direction in semidefinite programming
19. SDPT3-a MATLAB software package for semidefinite programming, version 1.3
20. On extending some primal-dual interior-point algorithms from linear programming to semidefinite programming
21. Semidefinite programming relaxations for the quadratic assignment problem