Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
Large clusters of mutual dependence have long been regarded as a problem impeding comprehension, testing, maintenance, and reverse engineering. An effective visualization can aid ...
Secure multiparty computation (MPC) allows joint privacy-preserving computations on data of multiple parties. Although MPC has been studied substantially, building solutions that ...
Martin Burkhart, Mario Strasser, Dilip Many, Xenof...
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...
While much research has been performed on query logs collected for major Web search engines, query log analysis to enhance search on smaller and more focused collections has attrac...
Stephen Dignum, Udo Kruschwitz, Maria Fasli, Yunhy...