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» Sparse Optimization for Second Order Kernel Methods
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GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
13 years 11 months ago
Evolutionary learning with kernels: a generic solution for large margin problems
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
Ingo Mierswa
ICASSP
2010
IEEE
13 years 7 months ago
Reconstruction of sparse signals from distorted randomized measurements
In this paper we show that, surprisingly, it is possible to recover sparse signals from nonlinearly distorted measurements, even if the nonlinearity is unknown. Assuming just that...
Petros Boufounos
SIAMSC
2008
131views more  SIAMSC 2008»
13 years 7 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
CVPR
2010
IEEE
14 years 3 months ago
Specular Surface Reconstruction from Sparse Reflection Correspondences
We present a practical approach for surface reconstruction of smooth mirror-like objects using sparse reflection correspondences (RCs). Assuming finite object motion with a fix...
Aswin Sankaranarayanan, Ashok Veeraraghavan, Oncel...
CSC
2006
13 years 8 months ago
Applying Sparse Matrix Solvers to a Glacial Ice Sheet Model
- Two software packages for solving sparse systems of linear equations, SuperLU and UMFPACK, have been integrated with the University of Maine Ice Sheet Model for predicting the fo...
Rodney Jacobs, James Fastook, Aitbala Sargent