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» On the Low Rank Solutions for Linear Matrix Inequalities
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MOR
2008
110views more  MOR 2008»
13 years 4 months ago
On the Low Rank Solutions for Linear Matrix Inequalities
In this paper we present a polynomial-time procedure to find a low rank solution for a system of Linear Matrix Inequalities (LMI). The existence of such a low rank solution was sh...
Wenbao Ai, Yongwei Huang, Shuzhong Zhang
SIAMSC
2011
219views more  SIAMSC 2011»
12 years 11 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
AUTOMATICA
2006
137views more  AUTOMATICA 2006»
13 years 4 months ago
A Newton-like method for solving rank constrained linear matrix inequalities
This paper presents a Newton-like algorithm for solving systems of rank constrained linear matrix inequalities. Though local quadratic convergence of the algorithm is not a priori...
Robert Orsi, Uwe Helmke, John B. Moore
SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
13 years 11 months ago
A Convex Approach to Low Rank Matrix Approximation with Missing Data
Many computer vision problems can be formulated as low rank bilinear minimization problems. One reason for the success of these problems is that they can be efficiently solved usin...
Carl Olsson, Magnus Oskarsson
MP
2011
12 years 11 months ago
Null space conditions and thresholds for rank minimization
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
Benjamin Recht, Weiyu Xu, Babak Hassibi