Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
We examine secure computing paradigms to identify any new architectural challenges for future general-purpose processors. Some essential security functions can be provided by diffe...
Semantic taxonomies such as WordNet provide a rich source of knowledge for natural language processing applications, but are expensive to build, maintain, and extend. Motivated by...