In this paper we propose a new class of attacks that exploit advertising systems offering microtargeting capabilities in order to breach user privacy. We study the advertising syst...
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...