We explore in this paper a progressive sampling algorithm, called Sampling Error Estimation (SEE), which aims to identify an appropriate sample size for mining association rules. S...
This paper investigates wireless sensor networks where a small percentage of nodes are assumed to know their location a priori. These reference nodes enable absolute localization ...
The class of dual φ-divergence estimators (introduced in Broniatowski and Keziou (2009) [6]) is explored with respect to robustness through the influence function approach. For ...
This paper presents a technique for high-level power estimation of microprocessors. The technique, which is based on abstract execution profiles called ’event signatures’, op...
We consider the problem of sensor selection so as to minimise error in estimated location of target. An algorithm based on selecting a sensor in a direction in which the error is ...