139 search results - page 28 / 28 » Learning Bayesian Network Structure using LP Relaxations |
KDD
2009
ACM
14 years 10 months ago
2009
ACM
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
CORR
2010
Springer
13 years 10 months ago
2010
Springer
Many firms these days, forced by increasing international competition and an unstable economy, are opting to specialize rather than generalize as a way of maintaining their compet...
JAIR
2010
13 years 8 months ago
2010
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
AAAI
2000
13 years 11 months ago
2000
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...