Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching

Hongteng Xu, Dixin Luo, Lawrence Carin

Oct-2-2025, 23:08:32 GMT–Neural Information Processing Systems

We propose a scalable Gromov-Wasserstein learning (S-GWL) method and establish a novel and theoretically-supported paradigm for large-scale graph analysis.

artificial intelligence, data mining, machine learning, (18 more...)

Neural Information Processing Systems

Oct-2-2025, 23:08:32 GMT

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  - Artificial Intelligence
    - Machine Learning (1.00)
    - Representation & Reasoning (1.00)
  - Data Science > Data Mining (1.00)

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Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching

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