702 search results - page 4 / 141 » Learning Probabilistic Models of Relational Structure |
70
Voted
ACL
2003
14 years 11 months ago
2003
This paper presents a dependency language model (DLM) that captures linguistic constraints via a dependency structure, i.e., a set of probabilistic dependencies that express the r...
IJCV
2010
14 years 8 months ago
2010
Humans demonstrate a remarkable ability to parse complicated motion sequences into their constituent structures and motions. We investigate this problem, attempting to learn the st...
ICML
2005
IEEE
15 years 11 months ago
2005
IEEE
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
92
Voted
KDD
2002
ACM
15 years 10 months ago
2002
ACM
Relational Markov models (RMMs) are a generalization of Markov models where states can be of different types, with each type described by a different set of variables. The domain ...
109
Voted
ICMLA
2009
14 years 8 months ago
2009
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...