660 search results - page 7 / 132 » A general filter for measurements with any probability distr... |
UAI
2000
13 years 8 months ago
2000
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
AUTOMATICA
2008
13 years 7 months ago
2008
We consider a discrete time state estimation problem over a packet-based network. In each discrete time step, a measurement packet is sent across a lossy network to an estimator u...
EOR
2010
13 years 7 months ago
2010
We consider the problem of accurately measuring the credit risk of a portfolio consisting of loans, bonds and other financial assets. One particular performance measure of interes...
FLAIRS
2006
13 years 9 months ago
2006
In real-life decision analysis, the probabilities and values of consequences are in general vague and imprecise. One way to model imprecise probabilities is to represent a probabi...