DocumentCode :
3721272
Title :
Approximate regularization paths for nuclear norm minimization using singular value bounds
Author :
N. Blomberg;C.R. Rojas;B. Wahlberg
Author_Institution :
Department of Automatic Control and ACCESS Linnaeus Center, School of Electrical Engineering, KTH-Royal Institute of Technology, SE-100 44 Stockholm, Sweden
fYear :
2015
Firstpage :
190
Lastpage :
195
Abstract :
The widely used nuclear norm heuristic for rank minimization problems introduces a regularization parameter which is difficult to tune. We have recently proposed a method to approximate the regularization path, i.e., the optimal solution as a function of the parameter, which requires solving the problem only for a sparse set of points. In this paper, we extend the algorithm to provide error bounds for the singular values of the approximation. We exemplify the algorithms on large scale benchmark examples in model order reduction. Here, the order of a dynamical system is reduced by means of constrained minimization of the nuclear norm of a Hankel matrix.
Keywords :
"Optimized production technology","Minimization","Benchmark testing","Heating"
Publisher :
ieee
Conference_Titel :
Signal Processing and Signal Processing Education Workshop (SP/SPE), 2015 IEEE
Type :
conf
DOI :
10.1109/DSP-SPE.2015.7369551
Filename :
7369551
Link To Document :
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