Random perturbation is a promising technique for privacy preserving data mining. It retains an original sensitive value with a certain probability and replaces it with a random va...
We consider the problem of computing information theoretic functions such as entropy on a data stream, using sublinear space. Our first result deals with a measure we call the &quo...
In this paper we investigate the usage of random ortho-projections in the compression of sparse feature vectors. The study is carried out by evaluating the compressed features in ...
This paper presents the axioms of a real time random walk on the set of states of a medium and some of their consequences, such as the asymptotic probabilities of the states. The ...
To anticipate and prevent acts of terrorism, Indications and Warnings analysts try to connect clues gleaned from massive quantities of complex data. Multi-agent approaches to supp...
Peter Weinstein, H. Van Dyke Parunak, Paul Chiusan...