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Review

2019

Review

2019

In recent years, optimization theory has been greatly impacted by the advent of sum of squares (SOS) optimization. The reliance… Expand

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Highly Cited

2009

Highly Cited

2009

We describe a major update of our Matlab freeware GloptiPoly for parsing generalized problems of moments and solving them… Expand

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Highly Cited

2006

Highly Cited

2006

An SDP relaxation based method is developed to solve the localization problem in sensor networks using incomplete and inaccurate… Expand

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Highly Cited

2003

Highly Cited

2003

Abstract. A hierarchy of convex relaxations for semialgebraic problems is introduced. For questions reducible to a finite number… Expand

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Highly Cited

2003

Highly Cited

2003

Abstract. This paper discusses computational experiments with linear optimization problems involving semidefinite, quadratic, and… Expand

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Highly Cited

2002

Highly Cited

2002

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among… Expand

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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… Expand

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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… Expand

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Highly Cited

1998

Highly Cited

1998

In this paper we consider semidefinite programs (SDPs) whose data depend on some unknown but bounded perturbation parameters. We… Expand

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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… Expand

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