Generative models of pattern individuality attempt to represent the distribution of observed quantitative features, e.g., by learning parameters from a database, and then use such...
This paper is about the Oblivious Transfer in the distributed model proposed by M. Naor and B. Pinkas. In this setting a Sender has n secrets and a Receiver is interested in one o...
Carlo Blundo, Paolo D'Arco, Alfredo De Santis, Dou...
Random linear network codes can be designed and implemented in a distributed manner, with low computational complexity. However, these codes are classically implemented [1] over fi...
In this paper, we present a Dynamic Load Balancing (DLB) policy for problems characterized by a highly irregular search tree, whereby no reliable workload prediction is available....
Distributed averaging describes a class of network algorithms for the decentralized computation of aggregate statistics. Initially, each node has a scalar data value, and the goal...