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: 12423
Venue: VLDB
Year: 2021
Pagerank: 6.4242e-05
Overall Rank: 4,126 | 71.33%
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
1,162	Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks	2022	VLDB	0.00013573136
3,715	Zebra: When Temporal Graph Neural Networks Meet Temporal Personalized PageRank	2023	VLDB	6.8176818e-05
5,007	Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning	2022	VLDB	5.7581517e-05
6,479	EARLY: Efficient and Reliable Graph Neural Network for Dynamic Graphs	2023	SIGMOD	5.0405101e-05
8,507	Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense	2024	VLDB	4.4909322e-05
9,095	Scapin: Scalable Graph Structure Perturbation by Augmented Influence Maximization	2023	SIGMOD	4.3925641e-05
9,766	View-based Explanations for Graph Neural Networks	2024	SIGMOD	4.2815042e-05
11,083	Fast and Space-Efficient Parallel Algorithms for Influence Maximization	2024	VLDB	4.1905499e-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
2,845	VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition	2021	VLDB	8.0301674e-05
6,553	Reliable Data Distillation on Graph Convolutional Network	2020	SIGMOD	5.0100594e-05
6,624	ALG: Fast and Accurate Active Learning Framework for Graph Convolutional Networks	2021	SIGMOD	4.9841936e-05

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