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Parallel implementations of probabilistic inference

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2 Author(s)
A. V. Kozlov ; Dept. of Applied Phys., Stanford Univ., CA, USA ; J. P. Singh

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

Published in:

Computer  (Volume:29 ,  Issue: 12 )