Abstract. In this paper we consider the dictionary problem in the scalable distributed data structure paradigm introduced by Litwin, Neimat and Schneider and analyze costs for inse...
We consider the problem of maintaining frequency counts for items occurring frequently in the union of multiple distributed data streams. Na?ive methods of combining approximate f...
Amit Manjhi, Vladislav Shkapenyuk, Kedar Dhamdhere...
An advanced high-level approach for programming of real-time distributed computing applications, the TMO (Time-triggered Message-triggered Object) programming and specification sc...
: In this paper we describe a similarity model that provides the objective basis for clustering proteins of similar structure. More specifically, we consider the following variant ...
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...