Given a percentage-threshold and readings from a pair of consecutive upstream and downstream sensors, flow anomaly discovery identifies dominant time intervals where the fractio...
James M. Kang, Shashi Shekhar, Christine Wennen, P...
Abstract— Meta-Learning has been used to predict the performance of learning algorithms based on descriptive features of the learning problems. Each training example in this cont...
Detecting outliers in data is an important problem with interesting applications in a myriad of domains ranging from data cleaning to financial fraud detection and from network i...
Gustavo Henrique Orair, Carlos Teixeira, Ye Wang, ...
Abstract-- Recent work has demonstrated that readings provided by commodity sensor nodes are often of poor quality. In order to provide a valuable sensory infrastructure for monito...
Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...