ARM-Net: Adaptive Relation Modeling Network for Structured Data
Summary: ARM-Net enables adaptive cross-feature modeling for structured data via exponential-space transforms and sparse attention. ARMOR, a lightweight relational analytics framework, delivers interpretable, per-tuple cross-feature usage with real-world gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Shaofeng Cai (National University of Singapore)
- 2. Kaiping Zheng (National University of Singapore)
- 3. Gang Chen (Zhejiang University)
- 4. H. V. Jagadish (University of Michigan)
- 5. Beng Chin Ooi (National University of Singapore)
- 6. Meihui Zhang (Beijing Institute of Technology)
BibTeX Citation
@inproceedings{cai_sigmod21,
title = {{ARM-Net: Adaptive Relation Modeling Network for Structured Data}},
author = {Cai, Shaofeng and Zheng, Kaiping and Chen, Gang and Jagadish, H. V. and Ooi, Beng Chin and Zhang, Meihui},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457321},
url = {https://dl.acm.org/doi/10.1145/3448016.3457321},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 835 | Scaling Factorization Machines to Relational Data | 2013 | VLDB | 0.00013721583 |
| 1,235 | Towards Linear Algebra over Normalized Data | 2017 | VLDB | 0.00011548457 |
| 2,179 | Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra | 2019 | SIGMOD | 9.0146333e-05 |
| 4,609 | F-IVM: Learning over Fast-Evolving Relational Data | 2020 | SIGMOD | 6.6081313e-05 |
| 8,352 | PACE: Learning Effective Task Decomposition for Human-in-the-loop Healthcare Delivery | 2021 | SIGMOD | 5.4453394e-05 |
| 11,789 | TRACER: A Framework for Facilitating Accurate and Interpretable Analytics for High Stakes Applications | 2020 | SIGMOD | 5.093636e-05 |
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