Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
Abstract. This paper establishes the foundation for the performance measurements of privacy preserving data mining techniques. The performance is measured in terms of the accuracy ...
In recent years, privacy preserving data mining has become an important problem because of the large amount of personal data which is tracked by many business applications. In many...
Data integration has been a long standing challenge to the database and data mining communities. This need has become critical in numerous contexts, including building e-commerce ...
Sourav S. Bhowmick, Le Gruenwald, Mizuho Iwaihara,...
Data mining tasks such as supervised classification can often benefit from a large training dataset. However, in many application domains, privacy concerns can hinder the construc...