We present algorithms for fast quantile and frequency estimation in large data streams using graphics processor units (GPUs). We exploit the high computational power and memory ba...
Naga K. Govindaraju, Nikunj Raghuvanshi, Dinesh Ma...
There are many application classes where the users are flexible with respect to the output quality. At the same time, there are other constraints, such as the need for real-time ...
Data streaming applications, usually composed with sequential/parallel tasks in a data pipeline form, bring new challenges to task scheduling and resource allocation in grid envir...
Concept drifting in data streams often occurs unpredictably at any time. Currently many classification mining algorithms deal with this problem by using an incremental learning ap...
A pattern is considered useful if it can be used to help a person to achieve his goal. Mining data streams for useful patterns is important in many applications. However, data stre...