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ICMLA
2007
13 years 6 months ago
Learning bayesian networks consistent with the optimal branching
We introduce a polynomial-time algorithm to learn Bayesian networks whose structure is restricted to nodes with in-degree at most k and to edges consistent with the optimal branch...
Alexandra M. Carvalho, Arlindo L. Oliveira
IJAR
2010
130views more  IJAR 2010»
13 years 3 months ago
Learning locally minimax optimal Bayesian networks
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...
Tomi Silander, Teemu Roos, Petri Myllymäki
ICML
2009
IEEE
14 years 5 months ago
Structure learning of Bayesian networks using constraints
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
ICAART
2010
INSTICC
14 years 1 months ago
Complexity of Stochastic Branch and Bound Methods for Belief Tree Search in Bayesian Reinforcement Learning
There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most...
Christos Dimitrakakis
IFIP12
2008
13 years 6 months ago
Bayesian Networks Optimization Based on Induction Learning Techniques
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...
Paola Britos, Pablo Felgaer, Ramón Garc&iac...