33 search results - page 2 / 7 » A Recursive Model-Reduction Method for Approximate Inference... |
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
EMMCVPR
2005
Springer
2005
Springer
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
13 years 10 months ago
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
ECCV
2008
Springer
14 years 6 months ago
2008
Springer
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
CVPR
2007
IEEE
14 years 7 months ago
2007
IEEE
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
ECCV
2006
Springer
14 years 6 months ago
2006
Springer
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...