564 search results - page 12 / 113 » Approximation algorithms for restricted Bayesian network str... |
155
click to vote
EWRL
2008
15 years 2 months ago
2008
A wide variety of function approximation schemes have been applied to reinforcement learning. However, Bayesian filtering approaches, which have been shown efficient in other field...
116
click to vote
NECO
2008
15 years 12 days ago
2008
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
111
click to vote
PPSN
2004
Springer
15 years 5 months ago
2004
Springer
Bayesian networks (BN) constitute a useful tool to model the joint distribution of a set of random variables of interest. To deal with the problem of learning sensible BN models fr...
121
Voted
UAI
2001
15 years 1 months ago
2001
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
103
click to vote
ICML
1996
IEEE
16 years 1 months ago
1996
IEEE
This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...