465 search results - page 11 / 93 » Active Learning for Parameter Estimation in Bayesian Network... |
91
Voted
IJAR
2010
14 years 8 months ago
2010
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
JMLR
2006
14 years 9 months ago
2006
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
95
Voted
AIIA
2003
Springer
15 years 2 months ago
2003
Springer
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...
NIPS
2004
14 years 11 months ago
2004
We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
UAI
1997
14 years 11 months ago
1997
We begin by discussing causal independence models and generalize these models to causal interaction models. Causal interaction models are models that have independent mechanisms w...