We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
We consider problems on data sets where each data point has uncertainty described by an individual probability distribution. We develop several frameworks and algorithms for calcul...
In this paper we consider the problem of efficiently locating cryptographic keys hidden in gigabytes of data, such as the complete file system of a typical PC. We describe efficie...
We present our work on using statistical, corpus-based machine learning techniques to simultaneously recognize an agent's current goal schemas at various levels of a hierarch...
: Probabilistic models for biological sequences (DNA and proteins) are frequently used in bioinformatics. We describe statistical tests designed to detect the order of dependency a...