In this work we provide efficient distributed protocols for generating shares of random noise, secure against malicious participants. The purpose of the noise generation is to crea...
Cynthia Dwork, Krishnaram Kenthapadi, Frank McSher...
In this paper we explore private computation built on vector addition and its applications in privacypreserving data mining. Vector addition is a surprisingly general tool for imp...
The ubiquity of the Internet has stimulated the development of data- rather than processor-intensive applications. Such data-intensive applications include streaming media, intera...
Gabriel Parmer, Richard West, Xin Qi, Gerald Fry, ...
We present a unified approach to locality optimization that employs both data and control transformations. Data transformations include changing the array layout in memory. Contr...
— The trend in Grid computing towards more data intensive applications, accessing more and more relational databases and requiring advanced integration of secondhand and publicly...