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 ...

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, ...

Streaming data, characterized by its temporal variations and large volumes, presents unique challenges for clustering tasks. To address these challenges, this paper proposes a novel weighted ...

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.