This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Abstract—In this paper, we investigate and analyze the expected per-node throughput in a wireless sensor network under a randomized sleep scheduling framework with a connectivity...
High performance computers currently under construction, such as IBM’s Blue Gene/L, consisting of large numbers (64K) of low cost processing elements with relatively small local...
Ed Upchurch, Paul L. Springer, Maciej Brodowicz, S...
As web-based online communities are rapidly growing, the agents in the communities need to know their measurable belief of trust for safe and successful interactions. In this pape...
The study of complex networks led to the belief that the connectivity of network nodes generally follows a Power-law distribution. In this work, we show that modeling large-scale ...
Alessandra Sala, Haitao Zheng, Ben Y. Zhao, Sabrin...