Data stream clustering algorithms play a pivotal role in the analysis of rapidly accumulating and evolving data sets, particularly as technologies such as the Internet of Things expand and generate ...

Data stream algorithms provide one-pass, memory-efficient techniques for processing continuous flows of network data. In network systems, these algorithms underpin tasks such as traffic monitoring, ...

Submodular maximization is a significant area of interest in combinatorial optimization, with numerous real-world applications. A research team led by Xiaoming SUN from the State Key Lab of Processors ...

Estimating the number of triangles in a graph is a fundamental problem and has found applications in many fields. This problem has been widely studied in the context of graph stream processing.

Data runs business. We’ve been told this now immutable truth countless times throughout the early dawn and later progression of the information age. The entire act of so-called digital transformation ...