Bayesian KnowledgeBases (BKB)are a rule-based probabilistic modelthat extend BayesNetworks(BN), by allowing context-sensitive independenceand cycles in the directed graph. BKBshav...
We analyze the amount of information needed to carry out model-based recognition tasks, in the context of a probabilistic data collection model, and independently of the recogniti...
— In this paper a new approach to optimize nuclear power plant designs based on global risk reduction are described. In design the focus is on as components quality as redundancy...
There exist many tools for capturing imprecision in probabilistic representations. Among them are random sets, possibility distributions, probability intervals, and the more recen...
We present a probabilistic analysis of integer linear programs (ILPs). More specifically, we study ILPs in a so-called smoothed analysis in which it is assumed that first an adve...