204 search results - page 1 / 41 » Learning locally minimax optimal Bayesian networks |
IJAR
2010
13 years 3 months ago
2010
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
We address the problem of Bayesian estimation where the statistical relation between the signal and measurements is only partially known. We propose modeling partial Baysian knowl...
ML
1998
ACM
13 years 4 months ago
1998
ACM
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
UAI
2003
13 years 6 months ago
2003
This paper proposes and evaluates the k-greedy equivalence search algorithm (KES) for learning Bayesian networks (BNs) from complete data. The main characteristic of KES is that i...
IFIP12
2008
13 years 6 months ago
2008
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...