Fast Partitioning for Distributed Graph Learning using Multi-level Label Propagation
Graph Neural Networks (GNNs) are a popular class of machine learning models that allow scientists to leverage machine learning techniques to perform inference on unstructured data. However, when graphs become too large, partitioning becomes necessary to allow for distributed computation. Standard gr...
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Format: | Thesis |
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Massachusetts Institute of Technology
2024
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Online Access: | https://hdl.handle.net/1721.1/153893 |