824 search results - page 5 / 165 » Learning probabilistic logic models from probabilistic examp... |
ETAI
2000
13 years 6 months ago
2000
Stochastic logic programs combine ideas from probabilistic grammars with the expressive power of definite clause logic; as such they can be considered as an extension of probabili...
SDM
2004
SIAM
13 years 7 months ago
2004
SIAM
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
IJCAI
2001
13 years 7 months ago
2001
We describe a framework that helps students learn from examples by generating example problem solutions whose level of detail is tailored to the students' domain knowledge. T...
KR
2004
Springer
13 years 11 months ago
2004
Springer
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...
ICML
2009
IEEE
14 years 7 months ago
2009
IEEE
In many real-world domains, undirected graphical models such as Markov random fields provide a more natural representation of the dependency structure than directed graphical mode...