220 search results - page 22 / 44 » Learning probabilistic decision graphs |
ATAL
2005
Springer
14 years 1 months ago
2005
Springer
This paper presents an agent strategy for complex bilateral negotiations over many issues with inter-dependent valuations. We use ideas inspired by graph theory and probabilistic ...
NN
1997
Springer
13 years 11 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
CVIU
2008
13 years 7 months ago
2008
We propose a novel scheme for using supervised learning for function-based classification of objects in 3D images. During the learning process, a generic multi-level hierarchical ...
ESOP
2011
Springer
12 years 11 months ago
2011
Springer
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
IJSI
2008
13 years 7 months ago
2008
Abstract In a line of recent development, probabilistic constructions of universal, homogeneous objects have been provided in various categories of ordered structures, such as caus...