The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...
3D neuro-anatomical images and other volumetric data sets are important in many scientific and biomedical fields. Since such sets may be extremely large, a scalable compression me...
Apriori Stochastic Dependency Detection (ASDD) is an algorithm for fast induction of stochastic logic rules from a database of observations made by an agent situated in an environm...
Linear optimization queries retrieve the top-K tuples in a sliding window of a data stream that maximize/minimize the linearly weighted sums of certain attribute values. To effici...
Stream compaction is a common parallel primitive used to remove unwanted elements in sparse data. This allows highly parallel algorithms to maintain performance over several proce...