Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization

Summary: Grain reframes GNN data selection as diversified influence maximization, merging propagation with social influence. It introduces a diversified objective and a greedy algorithm with guarantees, boosting learning and core-set efficiency on graphs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12422
Venue: VLDB
Year: 2021
Pagerank: 6.3921956e-05
Overall Rank: 4,165 | 71.03%
DOI: 10.14778/3476249.3476295

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
1,160	Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks	2022	VLDB	0.00013586221
3,709	Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank	2023	VLDB	6.8242482e-05
5,007	Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning	2022	VLDB	5.763689e-05
6,485	EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs	2023	SIGMOD	5.0453531e-05
8,510	Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense	2024	VLDB	4.4952414e-05
9,098	Scapin: Scalable Graph Structure Perturbation by Augmented Influence Maximization	2023	SIGMOD	4.3967784e-05
9,764	View-based Explanations for Graph Neural Networks	2024	SIGMOD	4.2856106e-05
11,080	Fast and Space-Efficient Parallel Algorithms for Influence Maximization	2024	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
2,839	VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition	2021	VLDB	8.0378978e-05
6,566	Reliable Data Distillation on Graph Convolutional Network	2020	SIGMOD	5.0074274e-05
6,625	ALG: Fast and Accurate Active Learning Framework for Graph Convolutional Networks	2021	SIGMOD	4.9889819e-05

Semantically Similar Papers

Overall Rank	Paper	Year	Venue	Pagerank
6,153	On Data-Aware Global Explainability of Graph Neural Networks	2023	VLDB	5.1829258e-05
2,400	ByteGNN: Efficient Graph Neural Network Training at Large Scale	2022	VLDB	8.8955105e-05
8,463	D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks	2024	VLDB	4.5052127e-05
10,011	A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness	2026	SIGMOD	4.1945683e-05
2,177	Accelerating Large Scale Real-Time GNN Inference using Channel Pruning	2021	VLDB	9.359876e-05
6,625	ALG: Fast and Accurate Active Learning Framework for Graph Convolutional Networks	2021	SIGMOD	4.9889819e-05
6,485	EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs	2023	SIGMOD	5.0453531e-05
3,087	Scalable and Efficient Full-Graph GNN Training for Large Graphs	2023	SIGMOD	7.5939896e-05
5,737	Comprehensive Evaluation of GNN Training Systems: A Data Management Perspective	2024	VLDB	5.3480667e-05
6,942	Efficient Training of Graph Neural Networks on Large Graphs	2024	VLDB	4.8922884e-05