Understand
We present a parallel approximation algorithm for a class of mixed packing and covering semidefinite programs which generalize on the class of positive semidefinite programs as considered by Jain and Yao [2011].
- As a corollary we get a faster approximation algorithm for positive semidefinite programs with better dependence of the parallel running time on the approximation factor, as compared to that of Jain and Yao [2011].
- Our algorithm and analysis is on similar lines as that of Young [2001] who considered analogous linear programs.
Built on
A parallel approximation algorithm for positive linear programming
M. Luby and N. Nisan · 1993
Earlier work this paper cites.
Sequential and parallel algorithms for mixed packing and covering
N. E. Young · 2001
Earlier work this paper cites.
Fast algorithms for approximate semidefinite programming using the multiplicative weights update method
S. Arora, E. Hazan, and S. Kale · 2005
Earlier work this paper cites.
A combinatorial, primal-dual approach to semidefinite programs
S. Arora and S. Kale · 2007
Earlier work this paper cites.
Similar
Efficient algorithms using the multiplicative weights update method
S. Kale · 2007
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Two-message quantum interactive proofs are in PSPACE
R. Jain, S. Upadhyay, and J. Watrous · 2009
Cited alongside, same era.
Parallel approximation of non-interactive zero-sum quantum games
R. Jain and J. Watrous · 2009
Cited alongside, same era.
Then
QIP = PSPACE
R. Jain, Z. Ji, S. Upadhyay, and J. Watrous · 2010
Later among the works it cites.
A parallel approximation algorithm for positive semidefinite programming
R. Jain and P. Yao · 2011
Later among the works it cites.
Faster and Simpler Width-Independent Parallel Algorithms for Positive Semidefinite Programming
R. Peng and K. Tangwongsan · 2012
Closest in time.
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