Abstract. Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or appr...
Protocols that provide reliable communicationon top of a network that can lose packets rely on periodically retransmitting packets. The choice of retransmission timeout critically...
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
This paper describes an adaptive noise cancellation structure suitable for the separation and equalization of signals that coupled due to the approximate placing of primary and au...
: We presentdesign-for-low-power techniques based on glitch reduction for register-transfer level circuits. We analyze the generation and propagation of glitches in both the contro...