Similar to verifiable shuffling (or, mixing), we consider the problem of verifiable rotating (and random re-encrypting) a given list of homomorphic encryptions. The offset by which...
Sebastiaan de Hoogh, Berry Schoenmakers, Boris Sko...
APPEARED IN ACM PODS-2009. A sliding windows model is an important case of the streaming model, where only the most "recent" elements remain active and the rest are disc...
Vladimir Braverman, Rafail Ostrovsky, Carlo Zaniol...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
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, ...
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we prop...