Randomization has been a primary tool to hide sensitive private information during privacy preserving data mining.The previous work based on spectral filtering, show the noise ma...
Spectral data often have a large number of highly-correlated features, making feature selection both necessary and uneasy. A methodology combining hierarchical constrained clusteri...
We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
Spectral clustering and path-based clustering are two recently developed clustering approaches that have delivered impressive results in a number of challenging clustering tasks. ...
Privacy is becoming an increasingly important issue in many data mining applications. This has triggered the development of many privacy-preserving data mining techniques. A large...