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CGF
2007
145views more  CGF 2007»
15 years 6 months ago
Data-driven Tetrahedral Mesh Subdivision
Given a tetrahedral mesh immersed in a voxel model, we present a method to refine the mesh to reduce the discrepancy between interpolated values based on either scheme at arbitra...
L. Rodriguez, Isabel Navazo, Alvar Vinacua
SIAMJO
2008
57views more  SIAMJO 2008»
15 years 6 months ago
Universal Confidence Sets for Solutions of Optimization Problems
We consider random approximations to deterministic optimization problems. The objective function and the constraint set can be approximated simultaneously. Relying on concentratio...
Silvia Vogel
AUTOMATICA
2002
93views more  AUTOMATICA 2002»
15 years 6 months ago
A probabilistic framework for problems with real structured uncertainty in systems and control
The objective of this paper is twofold. First, the problem of generation of real random matrix samples with uniform distribution in structured (spectral) norm bounded sets is stud...
Giuseppe Carlo Calafiore, Fabrizio Dabbene
MP
2002
93views more  MP 2002»
15 years 6 months ago
Conditioning of convex piecewise linear stochastic programs
In this paper we consider stochastic programming problems where the objective function is given as an expected value of a convex piecewise linear random function. With an optimal s...
Alexander Shapiro, Tito Homem-de-Mello, Joocheol K...
JMLR
2012
13 years 9 months ago
Lifted coordinate descent for learning with trace-norm regularization
We consider the minimization of a smooth loss with trace-norm regularization, which is a natural objective in multi-class and multitask learning. Even though the problem is convex...
Miroslav Dudík, Zaïd Harchaoui, J&eacu...