A key challenge faced by large-scale, distributed applications in Grid environments is efficient, seamless data management. In particular, for applications that can benefit from a...
Jithendar Paladugula, Ming Zhao 0002, Renato J. O....
Protein data contain discriminative patterns that can be used in many beneficial applications if they are defined correctly. In this work sequential pattern mining (SPM) is utiliz...
Themis P. Exarchos, Costas Papaloukas, Christos La...
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
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...
Random projections have recently emerged as a powerful method for dimensionality reduction. Theoretical results indicate that the method preserves distances quite nicely; however,...