Data-flow analysis is a common technique to gather program information for use in transformations such as register allocation, dead-code elimination, common subexpression elimina...
Wireless sensor networks are proving to be useful in a variety of settings. A core challenge in these networks is to minimize energy consumption. Prior database research has propo...
David Chu, Amol Deshpande, Joseph M. Hellerstein, ...
Recently, there has been an increasing interest in the investigation of statistical pattern recognition models for the fully automatic segmentation of the left ventricle (LV) of t...
The problem of identifying deviating patterns in XML repositories has important applications in data cleaning, fraud detection, and stock market analysis. Current methods determine...
We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...