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Efficient Tree-SVD for Subset Node Embedding over Large Dynamic Graphs

Summary: Tree-SVD fuses sparse randomized SVD with hierarchical SVD to efficiently update subset embeddings on large dynamic graphs. A lazy-update strategy updates only sub-matrices that change significantly (Frobenius norm), with theoretical guarantees and strong results on node classification and link prediction. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6661
Venue
SIGMOD
Year
2023
Pagerank
6.1548101e-05
Overall Rank
5,596 | 61.61%
DOI
10.1145/3588950

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{du_sigmod23,
        title = {{Efficient Tree-SVD for Subset Node Embedding over Large Dynamic Graphs}},
        author = {Du, Xinyu and Zhang, Xingyi and Wang, Sibo and Huang, Zengfeng},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3588950},
        url = {https://dl.acm.org/doi/10.1145/3588950},
        year = {2023}
}

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