5 search results - page 1 / 1 » Inferring Finite Automata with Stochastic Output Functions a... |
AAAI
1992
13 years 6 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
13 years 8 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
13 years 12 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 4 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 days 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 ...