We describe a query-driven indexing framework for scalable text retrieval over structured P2P networks. To cope with the bandwidth consumption problem that has been identified as ...
Gleb Skobeltsyn, Toan Luu, Karl Aberer, Martin Raj...
The shrinking processor feature size, lower threshold voltage and increasing clock frequency make modern processors highly vulnerable to transient faults. Architectural Vulnerabil...
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
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...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...