Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Abstract. This text is an informal review of several randomized algorithms that have appeared over the past two decades and have proved instrumental in extracting efficiently quant...
The need for Bayesian inference arises in military intelligence, medical diagnosis and many other practical applications. The problem is that human inferences are generally conserv...
We consider selected geometric properties of 2D or 3D sets, given in form of binary digital pictures, and discuss their estimation. The properties examined are perimeter and area i...
— Mobile ad hoc networks consist of nodes that are often vulnerable to failure. As such, it is important to provide redundancy in terms of providing multiple nodedisjoint paths f...
Zhenqiang Ye, Srikanth V. Krishnamurthy, Satish K....