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» On Constrained Sparse Matrix Factorization
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SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
15 years 4 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
SIAMSC
2008
131views more  SIAMSC 2008»
14 years 9 months ago
Gramian-Based Model Reduction for Data-Sparse Systems
Model order reduction (MOR) is common in simulation, control and optimization of complex dynamical systems arising in modeling of physical processes and in the spatial discretizati...
Ulrike Baur, Peter Benner
ICCAD
2009
IEEE
133views Hardware» more  ICCAD 2009»
14 years 7 months ago
A parallel preconditioning strategy for efficient transistor-level circuit simulation
A parallel computing approach for large-scale SPICE-accurate circuit simulation is described that is based on a new preconditioned iterative solver. The preconditioner involves the...
Heidi Thornquist, Eric R. Keiter, Robert J. Hoekst...
CIKM
2008
Springer
14 years 11 months ago
A consensus based approach to constrained clustering of software requirements
Managing large-scale software projects involves a number of activities such as viewpoint extraction, feature detection, and requirements management, all of which require a human a...
Chuan Duan, Jane Cleland-Huang, Bamshad Mobasher
CISS
2008
IEEE
15 years 4 months ago
1-Bit compressive sensing
Abstract—Compressive sensing is a new signal acquisition technology with the potential to reduce the number of measurements required to acquire signals that are sparse or compres...
Petros Boufounos, Richard G. Baraniuk