We propose two fast algorithms for abrupt change detection in streaming data that can operate on arbitrary unknown data distributions before and after the change. The first algor...
Privacy is one of the most important properties of an information system must satisfy. In which systems the need to share information among different, not trusted entities, the pro...
In this paper, we present an abstract framework for online approximation of time-series data that yields a unified set of algorithms for several popular models: data streams, amnes...
The discovery of complex patterns such as clusters, outliers, and associations from huge volumes of streaming data has been recognized as critical for many domains. However, patte...
Recently, there has been significant interest in developing space and time efficient solutions for answering continuous summarization queries over data streams. While these techni...
Nagender Bandi, Ahmed Metwally, Divyakant Agrawal,...