53 search results - page 4 / 11 » Expectation Propagation for approximate Bayesian inference |
JMLR
2010
13 years 4 days ago
2010
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
EMNLP
2006
13 years 6 months ago
2006
The end-to-end performance of natural language processing systems for compound tasks, such as question answering and textual entailment, is often hampered by use of a greedy 1-bes...
FLAIRS
2003
13 years 6 months ago
2003
We extend the differential approach to inference in Bayesian networks (BNs) (Darwiche, 2000) to handle specific problems that arise in the context of dynamic Bayesian networks (D...
PAMI
2006
13 years 5 months ago
2006
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
ICANN
2009
Springer
13 years 9 months ago
2009
Springer
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...