Burst detection is the activity of finding abnormal aggregates in data streams. Such aggregates are based on sliding windows over data streams. In some applications, we want to mo...
Skew is prevalent in data streams, and should be taken into account by algorithms that analyze the data. The problem of finding "biased quantiles"-- that is, approximate...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...
Abstract. We describe an algorithm for fitting a Catmull-Clark subdivision surface model to an unstructured, incomplete and noisy data set. We complete the large missing data regi...
Task Scheduling is a critical design issue of distributed computing. The emerging Grid computing infrastructure consists of heterogeneous resources in widely distributed autonomous...
This paper presents research-in-progress. An extensive customer-centric data warehouse architecture should enable both complex analytical queries as well as standard reporting que...