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We point out some connections between applications of semidefinite programming in control and in combinatorial optimization. In both fields semidefinite programs arise as convex relaxations of NP-hard...
We present an overview of the essential elements of semidefinite programming as a computational tool for the analysis of systems and control problems. We make particular emphasis on general duality pr...
We investigate the use of linear programming tools for solving semidefinite programming relaxations of quadratically constrained quadratic problems. Classes of valid linear inequalities are presented,...
A Sequence of Relaxations Constraining Hidden Variable Models     Hidden Variable Models  Relaxations       font style='font-size:12px;'> 2011/9/13
Many widely studied graphical models with latent variables lead to nontrivial constraints on the distribution of the observed variables.Inspired by the Bell inequalities in quantum mechanics, we refer...
Abstract: We investigate the Sherali-Adams lift & project hierarchy applied to a graph isomorphism polytope whose integer points encode the isomorphisms between two graphs. In particular, the Sherali-...
Sparse PCA: Convex Relaxations, Algorithms and Applications     Sparse PCA  Algorithms  Applications       font style='font-size:12px;'> 2010/11/22
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonzero coefficients in th...

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