Protecting data privacy is an important problem in microdata distribution. Anonymization algorithms typically aim to protect individual privacy, with minimal impact on the quality...
Kristen LeFevre, David J. DeWitt, Raghu Ramakrishn...
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
Pattern ordering is an important task in data mining because the number of patterns extracted by standard data mining algorithms often exceeds our capacity to manually analyze the...
Power-Efficient DRAM Speculation (PEDS) is a power optimization targeted at broadcast-based sharedmemory multiprocessor systems that speculatively access DRAM in parallel with the...
Nidhi Aggarwal, Jason F. Cantin, Mikko H. Lipasti,...