Title :
Parallel implementations of probabilistic inference
Author :
Kozlov, Alexander V. ; Singh, Jay Prakash
Author_Institution :
Dept. of Applied Phys., Stanford Univ., CA, USA
fDate :
12/1/1996 12:00:00 AM
Abstract :
Probabilistic inference is becoming an integral part of decision-making systems, but it is so computationally intensive that it is often impractical. The authors report on the effectiveness of speeding up this technique by exploiting its parallelism
Keywords :
decision support systems; inference mechanisms; parallel processing; probability; uncertainty handling; computationally intensive; decision-making systems; parallel implementations; probabilistic inference; uncertainty; Application software; Asia; Cancer; Concurrent computing; Decision making; Distributed computing; Lungs; Parallel processing; Testing; Uncertainty;
