305 search results - page 12 / 61 » Bayesian Learning of Markov Network Structure |
AIIA
2003
Springer
14 years 28 days ago
2003
Springer
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
The structure of a Bayesian network (BN) encodes variable independence. Learning the structure of a BN, however, is typically of high computational complexity. In this paper, we e...
ECCV
2010
Springer
14 years 25 days ago
2010
Springer
We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image feature...
JETAI
1998
13 years 7 months ago
1998
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...