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
In this paper, we present an abstract framework for online approximation of time-series data that yields a unified set of algorithms for several popular models: data streams, amnes...
With advances in process technology, soft errors (SE) are becoming an increasingly critical design concern. Due to their large area and high density, caches are worst hit by soft ...
We investigate the space requirements for summaries needed for maintaining exact answers to aggregate queries over histories of relational databases. We show that, in general, a su...
We introduce Pulse, a framework for processing continuous queries over models of continuous-time data, which can compactly and accurately represent many real-world activities and p...