ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling
Summary: ADGNN enables scalable full-batch GNN training with a hybrid sampling engine in distributed systems. It introduces Aggregation Difference (AD) to bound sampling impact, plus AD-Sampling with adaptive sampling and AD-importance sampling for remote nodes, with result reuse; achieving up to 9x efficiency and similar accuracy. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhen Song
- 2. Yu Gu
- 3. Tianyi Li
- 4. Qing Sun
- 5. Yanfeng Zhang
- 6. Christian S. Jensen
- 7. Ge Yu
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,710 | DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training | 2024 | VLDB | 5.3590055e-05 |
| 10,011 | A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness | 2026 | SIGMOD | 4.1945683e-05 |
| 10,506 | SWASH: A Flexible Communication Framework with Sliding Window-Based Cache Sharing for Scalable DGNN Training | 2025 | SIGMOD | 4.1945683e-05 |
| 10,539 | Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch. | 2025 | VLDB | 4.1945683e-05 |
| 10,735 | Faster Convergence in Mini-batch Graph Neural Networks Training with Pseudo Full Neighborhood Compensation | 2025 | VLDB | 4.1945683e-05 |
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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 |
|---|---|---|---|---|
| 278 | AliGraph: A Comprehensive Graph Neural Network Platform | 2019 | VLDB | 0.00029230623 |
| 1,329 | AGL: A Scalable System for Industrial-purpose Graph Machine Learning | 2020 | VLDB | 0.00012561848 |
| 2,422 | DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU | 2023 | SIGMOD | 8.8499665e-05 |
| 3,025 | NeutronStar: Distributed GNN Training with Hybrid Dependency Management | 2022 | SIGMOD | 7.6906935e-05 |
| 3,087 | Scalable and Efficient Full-Graph GNN Training for Large Graphs | 2023 | SIGMOD | 7.5939896e-05 |
| 4,047 | Orca: Scalable Temporal Graph Neural Network Training with Theoretical Guarantees | 2023 | SIGMOD | 6.4972105e-05 |
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