Abstract. Internet coordinate systems appear promising as a method for estimating network distance without direct measurement, allowing scalable configuration of emerging applicat...
Given observed data and a collection of parameterized candidate models, a 1- confidence region in parameter space provides useful insight as to those models which are a good fit t...
Brent Bryan, H. Brendan McMahan, Chad M. Schafer, ...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
The queueing Petri net (QPN) paradigm provides a number of benefits over conventional modeling paradigms such as queueing networks and generalized stochastic Petri nets. Using qu...
This paper describes a continuous estimation of distribution algorithm (EDA) to solve decomposable, real-valued optimization problems quickly, accurately, and reliably. This is the...
Chang Wook Ahn, Rudrapatna S. Ramakrishna, David E...