Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
We are building a biomedical information resource consisting of digitized x-ray images and associated textual data from national health surveys. This resource, the Web-based Medic...
We consider the problem of joining data streams using limited cache memory, with the goal of producing as many result tuples as possible from the cache. Many cache replacement heu...
We present a formal model and a simple architecture for robust pseudorandom generation that ensures resilience in the face of an observer with partial knowledge/control of the gen...
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...