Logarithmic Time Parallel Bayesian Inference
نویسنده
چکیده
I present a parallel algorithm for exact prob abilistic inference in Bayesian networks. For polytree networks with n variables, the worst case time complexity is O(log n) on a CREW PRAM (concurrent-read, exclusive-write paral lel random-access machine) with n processors, for any constant number of evidence variables. For arbitrary networks, the time complexity is O( r3w log n) for n processors, or 0( w log n) for r3w n processors, where r is the maximum range of any variable, and w is the induced width (the maximum clique size), after moralizing and trian gulating the network.
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