5 search results - page 1 / 1 » Inferring Finite Automata with Stochastic Output Functions a... |
AAAI
1992
13 years 10 months ago
1992
It is often useful for a robot to construct a spatial representation of its environment from experiments and observations, in other words, to learn a map of its environment by exp...
COLT
2006
Springer
14 years 1 months ago
2006
Springer
Given a finite set of words w1, . . . , wn independently drawn according to a fixed unknown distribution law P called a stochastic language, an usual goal in Grammatical Inference ...
ICML
2009
IEEE
14 years 4 months ago
2009
IEEE
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
JAIR
1998
13 years 9 months ago
1998
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
CVPR
2009
IEEE
15 years 4 months ago
2009
IEEE
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...