Boosting is a general method for improving the accuracy of learning algorithms. We use boosting to construct improved privacy-preserving synopses of an input database. These are da...
This paper considers the construction and analysis of pseudo-random functions (PRFs) with specific reference to modes of operations of a block cipher. In the context of message aut...
In machine learning and computer vision, input signals are often filtered to increase data discriminability. For example, preprocessing face images with Gabor band-pass filters ...
Genetic linkage analysis is a challenging application which requires Bayesian networks consisting of thousands of vertices. Consequently, computing the likelihood of data, which i...
Accurate cardinality estimation is critically important to high-quality query optimization. It is well known that conventional cardinality estimation based on histograms or simila...