12 search results - page 2 / 3 » Learning, Regularization and Ill-Posed Inverse Problems |
UAI
2008
13 years 11 months ago
2008
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
PKDD
2010
Springer
13 years 8 months ago
2010
Springer
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
ESANN
2004
13 years 11 months ago
2004
This paper is based on a new way for determining the regularization trade-off in least squares support vector machines (LS-SVMs) via a mechanism of additive regularization which ha...
NIPS
2004
13 years 11 months ago
2004
We consider the problem of geometrical surface reconstruction from one or several images using learned shape models. While humans can effortlessly retrieve 3D shape information, t...
ICML
2005
IEEE
14 years 10 months ago
2005
IEEE
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...