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PGTuner: An Efficient Framework for Automatic and Transferable Configuration Tuning of Proximity Graphs

Summary: PGTuner pre-trains a query-performance predictor to avoid costly proximity-graph rebuilds and uses deep reinforcement learning to recommend optimal construction/query parameters for target accuracy. It adds OOD detection and active learning for efficient transfer to new/dynamic datasets, yielding up to 14.7× speedups. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
7336
Venue
SIGMOD
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,031 | 30.22%
DOI
10.1145/3749179

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

Rank Cited Paper Year Venue Pagerank
212 Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph 2019 VLDB 0.00033913475
514 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.0002124895
770 A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search 2021 VLDB 0.00016917602
782 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00016729063
1,364 Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination 2020 SIGMOD 0.00012370117
1,971 LazyLSH: Approximate Nearest Neighbor Search for Multiple Distance Functions with a Single Index 2016 SIGMOD 9.893198e-05
2,023 Efficient Approximate Nearest Neighbor Search in Multi-dimensional Databases 2023 SIGMOD 9.7544991e-05
2,971 Towards Efficient Index Construction and Approximate Nearest Neighbor Search in High-Dimensional Spaces 2023 VLDB 7.7970531e-05
4,399 HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements 2022 SIGMOD 6.2225151e-05
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