The growth of the Internet has triggered tremendous opportunities for cooperative
computation, where people are jointly conducting computation tasks based on the private …

Traditionally, a bottleneck preventing the development of more intelligent systems was the
limited amount of data available. Nowadays, the total amount of information is almost …

This paper introduces the problem of combining multiple partitionings of a set of objects into
a single consolidated clustering without accessing the features or algorithms that …

Various distributed optimization methods have been developed for solving problems which
have simple local constraint sets and whose objective function is the sum of local cost …

Motivation Limited data access has hindered the field of precision medicine from exploring
its full potential, eg concerning machine learning and privacy and data protection rules. Our …

This paper explores the possibility of using multiplicative random projection matrices for
privacy preserving distributed data mining. It specifically considers the problem of computing …

To address the problem of unsupervised outlier detection in wireless sensor networks, we
develop an approach that (1) is flexible with respect to the outlier definition,(2) computes the …

The paper summarizes the different characteristics of Web data, the basic components of
Web mining and its different types, and the current state of the art. The reason for …

Privacy is becoming an increasingly important issue in many data-mining applications. This
has triggered the development of many privacy-preserving data-mining techniques. A large …

Advances in computing and communication over wired and wireless networks have resulted
in many pervasive distributed computing environments. The Internet, intranets, local area …