The aggregation of conflicting preferences is an important issue in human society and multiagent systems. Due to its universality, voting among a set of alternatives has a centra...
Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
In this paper we study the problem of approximately releasing the cut function of a graph while preserving differential privacy, and give new algorithms (and new analyses of exis...
The aggregation of conflicting preferences is a key issue in multiagent systems. Due to its universality, voting has a central role among preference aggregation mechanisms. Votin...
There is a large gap between the theory and practice for random number generation. For example, on most operating systems, using /dev/random to generate a 256-bit AES key is highl...