We propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. We focus on the motivating application of pro...
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabh...
Background: Many analyses of microarray association studies involve permutation, bootstrap resampling and crossvalidation, that are ideally formulated as embarrassingly parallel c...
Ivo D. Shterev, Sin-Ho Jung, Stephen L. George, Ko...
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
We study non-parametric measures for the problem of comparing distributions, which arise in anomaly detection for continuous time series. Non-parametric measures take two distribu...
— We propose an implementable new universal lossy source coding algorithm. The new algorithm utilizes two wellknown tools from statistical physics and computer science: Gibbs sam...