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» Optimization of Convex Risk Functions
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ESANN
2001
14 years 4 days ago
Penalized least squares, model selection, convex hull classes and neural nets
We develop improved risk bounds for function estimation with models such as single hidden layer neural nets, using a penalized least squares criterion to select the size of the mod...
Gerald H. L. Cheang, Andrew R. Barron
FS
2011
95views more  FS 2011»
13 years 5 months ago
A note on the existence of the power investor's optimizer
[KLSX91] ensure the existence of the expected utility maximizer for investors with constant relative risk aversion coefficients less than one. In this note, we explain a simple tr...
Kasper Larsen
JMLR
2006
107views more  JMLR 2006»
13 years 10 months ago
Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss
The consistency of classification algorithm plays a central role in statistical learning theory. A consistent algorithm guarantees us that taking more samples essentially suffices...
Di-Rong Chen, Tao Sun
ECCV
2008
Springer
15 years 19 days ago
Integration of Multiview Stereo and Silhouettes Via Convex Functionals on Convex Domains
We propose a convex framework for silhouette and stereo fusion in 3D reconstruction from multiple images. The key idea is to show that the reconstruction problem can be cast as one...
Kalin Kolev, Daniel Cremers
MP
1998
134views more  MP 1998»
13 years 10 months ago
Second-order global optimality conditions for convex composite optimization
In recent years second-order sufficient conditions of an isolated local minimizer for convex composite optimization problems have been established. In this paper, second-order opt...
Xiaoqi Yang