We show how to uniformly distribute data at random (not to be confounded with permutation routing) in two settings that are able to deal with massive data: coarse grained parallel...
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Abstract—In this paper we propose a novel statistical framework to model the impact of process variations on semiconductor circuits through the use of process sensitive test stru...
We propose a Polynomial-based scheme that addresses the problem of Event Region Detection (PERD) for wireless sensor networks (WSNs). Nodes of an aggregation tree perform function ...
Torsha Banerjee, Demin Wang, Bin Xie, Dharma P. Ag...
One of the key points in Estimation of Distribution Algorithms (EDAs) is the learning of the probabilistic graphical model used to guide the search: the richer the model the more ...