An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data needs to be used repea...
Most previous research on privacy-preserving data publishing, based on the k-anonymity model, has followed the simplistic approach of homogeneously giving the same generalized val...
Wai Kit Wong, Nikos Mamoulis, David Wai-Lok Cheung
Tiny, low-cost sensor devices are expected to be failure-prone and hence in many realistic deployment scenarios for sensor networks these nodes are deployed in higher than necessa...
New static source routing algorithms for High Performance Computing (HPC) are presented in this work. The target parallel architectures are based on the commonly used fattree netw...
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we prop...