This paper is concerned with the problem of predicting relative performance of classification algorithms. It focusses on methods that use results on small samples and discusses th...
From a computational perspective, there is a close connection between various probabilistic reasoning tasks and the problem of counting or sampling satisfying assignments of a pro...
Abstract. We present a new technique for granular sampling using a pulsecoupled network of spiking artificial neurons to generate grain events. The system plays randomly selected s...
In this paper, we re-examine the RSSI measurement model for location estimation and provide the first detailed formulation of the probability distribution of the position of a sens...
Charalampos Papamanthou, Franco P. Preparata, Robe...
In this work, we present a technique for robust estimation, which by explicitly incorporating the inherent uncertainty of the estimation procedure, results in a more efficient rob...