143 search results - page 13 / 29 » Modeling Unreliable Observations in Bayesian Networks by Cre... |
NIPS
2008
13 years 9 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
SEMWEB
2005
Springer
14 years 1 months ago
2005
Springer
Probabilistic inference will be of special importance when one needs to know how much we can say with what all we know given new observations. Bayesian Network is a graphical prob...
AAAI
1996
1996
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
13 years 9 months ago
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
In most real-world situations, a single microphone is insufficient for the characterization of an entire auditory scene. This often occurs in places such as office environments ...
IROS
2008
IEEE
14 years 2 months ago
2008
IEEE
— In this paper, scalable collaborative human-robot systems for information gathering applications are approached as a decentralized Bayesian sensor network problem. Humancompute...