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Semidefinite programming relaxations of non-convex problems in control and combinatorial optimization
Applications of semidefinite programming combinatorial optimization quadratic semi-definite programming bilinear matrix inequality
2015/8/11
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...
Further relaxations of the semidefinite programming approach to sensor network localization
Semidefinite programming sensor networks positioning sensors
2015/8/10
Recently, a semidefinite programming (SDP) relaxation approach has been proposed to solve the sensor network localization problem. Although it achieves high accuracy in estimating the sensor locations...
Semidefinite Programming Relaxations of Non-Convex Problems in Control and Combinatorial Optimization
Semidefinite Programming Relaxations Non-Convex Problems Control Combinatorial Optimization
2015/7/13
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...
Further Relaxations of the Semidefinite Programming Approach to Sensor Network Localization
sensor network localization semidefi nite programming
2015/7/9
Recently, a semidefinite programming (SDP) relaxation approach has been proposed to solve the sensor network localization problem. Although it achieves high accuracy in estimating the sensor locations...
Semidefinite Programming Relaxations and Algebraic Optimization in Control
Control Algebraic Optimization
2015/6/19
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...
Group-Sparse Model Selection: Hardness and Relaxations
Signal Approximation Structured Sparsity Interpretability Tractability Dynamic Programming Compressive Sensing
2013/5/2
Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. The main promise of these model...
Linear Programming Relaxations of Quadratically Constrained Quadratic Programs
Quadratic Programming Semidefinite Programming relaxation Linear Programming
2012/6/29
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
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...
A Sequence of Relaxations Constraining Hidden Variable Models
Sequence Relaxations Constraining Hidden Variable Models
2011/7/6
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 refe...
Sherali-Adams Relaxations of Graph Isomorphism Polytopes
Sherali-Adams Relaxations Graph Isomorphism Polytopes Combinatorics
2011/8/24
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
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...