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...
We propose a non-parametric texture modeling and synthesis technique based on the integer version of the Discrete Wavelet Transform (DWT). The successive levels of the DWT pyramid...
Learning classifiers has been studied extensively the last two decades. Recently, various approaches based on patterns (e.g., association rules) that hold within labeled data hav...
In black-box testing, one is interested in creating a suite of tests from requirements that adequately exercise the behavior of a software system without regard to the internal st...
Michael W. Whalen, Ajitha Rajan, Mats Per Erik Hei...
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...