Exploiting Sparsity in SDP Relaxation for Sensor Network Localization
From MaRDI portal
Publication:5189557
DOI10.1137/080713380zbMath1190.65096OpenAlexW1983766376MaRDI QIDQ5189557
Hayato Waki, Kojima, Masakazu, Sunyoung Kim
Publication date: 17 March 2010
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/080713380
semidefinite programmingnumerical examplesquadratic optimizationsparsitypolynomial optimization problemsemidefinite relaxationsensor network localization problem
Programming involving graphs or networks (90C35) Numerical mathematical programming methods (65K05) Semidefinite programming (90C22) Quadratic programming (90C20)
Related Items
A block coordinate descent method for sensor network localization, On the bridge between combinatorial optimization and nonlinear optimization: a family of semidefinite bounds for 0--1 quadratic problems leading to quasi-Newton methods, Approximation accuracy, gradient methods, and error bound for structured convex optimization, Noisy Euclidean Distance Realization: Robust Facial Reduction and the Pareto Frontier, A simple globally convergent algorithm for the nonsmooth nonconvex single source localization problem, A facial reduction approach for the single source localization problem, Exact SDP relaxations for quadratic programs with bipartite graph structures, Enclosing ellipsoids and elliptic cylinders of semialgebraic sets and their application to error bounds in polynomial optimization, A DC programming approach for sensor network localization with uncertainties in anchor positions, Geometric buildup algorithms for sensor network localization, (Robust) edge-based semidefinite programming relaxation of sensor network localization, Computing the nearest Euclidean distance matrix with low embedding dimensions, Comparing SOS and SDP relaxations of sensor network localization, Edge-based semidefinite programming relaxation of sensor network localization with lower bound constraints, Exploiting sparsity in linear and nonlinear matrix inequalities via positive semidefinite matrix completion, Exploiting Sparsity in SDP Relaxation of Polynomial Optimization Problems, Euclidean Distance Matrices and Applications, Unconstrained minimization of block-circulant polynomials via semidefinite program in third-order tensor space, Selected Open Problems in Discrete Geometry and Optimization
Uses Software
