Heterogeneous graphs organize data with nodes and edges, and have been widely used in various graph-centric applications. Often, some data are omitted during manual construction, leading to data ...

Differential privacy (DP) stands as the gold standard for protecting user information in large-scale machine learning and data analytics. A critical task within DP is partition selection—the process ...

Abstract: Graph partitioning is a long-standing research problem and has applications in various domains, such as data mining, scientific computing, VLSI design. For many years researchers have been ...

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@InProceedings{kolountzakisEfficient2010, Title = {Efficient Triangle Counting in Large Graphs via Degree-based Vertex Partitioning}, author = {Mihail N. Kolountzakis and Gary L. Miller and Richard ...

Extracting knowledge by performing computations on graphs is becoming increasingly challenging as graphs grow in size. A standard approach distributes the graph over a cluster of nodes, but performing ...