42 search results - page 8 / 9 » Symbolic Probabilistic Inference in Belief Networks |
ICIP
2007
IEEE
14 years 9 months ago
2007
IEEE
The segmentation and recognition modules are usually implemented sequentially in most traditional automatic license recognition (LPR) systems. In this work, we integrate segmentat...
AAAI
2000
13 years 9 months ago
2000
Sampling has become an important strategy for inference in belief networks. It can also be applied to the problem of selecting actions in influence diagrams. In this paper, we pre...
JMLR
2010
13 years 2 months ago
2010
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
PAKDD
2005
ACM
14 years 1 months ago
2005
ACM
The usefulness of the results produced by data mining methods can be critically impaired by several factors such as (1) low quality of data, including errors due to contamination, ...
AAAI
2010
13 years 9 months ago
2010
Lifted inference, handling whole sets of indistinguishable objects together, is critical to the effective application of probabilistic relational models to realistic real world ta...