Semidefinite programming

Known as: Semi-definite programming, Semidefinite programs 
Semidefinite programming (SDP) is a subfield of convex optimization concerned with the optimization of a linear objective function (an objective… (More)
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Topic mentions per year

1970-2017
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Papers overview

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Highly Cited
2005
Highly Cited
2005
We analyze the semidefinite programming (SDP) based model and method for the position estimation problem in sensor network… (More)
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Highly Cited
2004
Highly Cited
2004
Can we detect low dimensional structure in high dimensional data sets of images? In this paper, we propose an algorithm for… (More)
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Highly Cited
2003
Highly Cited
2003
A hierarchy of convex relaxations for semialgebraic problems is introduced. For questions reducible to a finite number of… (More)
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Highly Cited
2000
Highly Cited
2000
A central drawback of primal-dual interior point methods for semidefinite programs is their lack of ability to exploit problem… (More)
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Highly Cited
2000
Highly Cited
2000
In the first part of this thesis, we introduce a specific class of Linear Matrix Inequalities (LMI) whose optimal solution can be… (More)
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Highly Cited
1997
Highly Cited
1997
We discuss the use of semidefinite programming for combinatorial optimization problems. The main topics covered include (i) the… (More)
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Highly Cited
1997
Highly Cited
1997
We present and motivate a new model of the truss topology design problem, where the rigidity of the resulting truss with respect… (More)
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Highly Cited
1996
Highly Cited
1996
We propose a new interior point based method to minimize a linear function of a matrix variable subject to linear equality and… (More)
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Highly Cited
1995
Highly Cited
1995
We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiability (MAX 2SAT) problems… (More)
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Highly Cited
1994
Highly Cited
1994
We consider the problem of coloring <italic>k</italic>-colorable graphs with the fewest possible colors. We present a randomized… (More)
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