A Neural Database for Differentially Private Spatial Range Queries

Summary: Neural database for differentially private spatial range queries; learns density-aware models that preserve spatial signal under DP noise. Public-data-driven parameter tuning; outperforms binning-based DP methods on real datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h833c271cfb9e5a7c
Venue: VLDB
Year: 2022
Pagerank: 5.9942738e-05
Overall Rank: 5,789 | 61.08%
DOI: 10.14778/3510397.3510404

Incoming Non-self Citations Over Time

Authors

1. Sepanta Zeighami (University of Southern California)
2. Ritesh Ahuja (University of Southern California)
3. Gabriel Ghinita (University of Massachusetts Boston)
4. Cyrus Shahabi (University of Southern California)

BibTeX Citation

@article{zeighami_vldb22,
        title = {{A Neural Database for Differentially Private Spatial Range Queries}},
        author = {Zeighami, Sepanta and Ahuja, Ritesh and Ghinita, Gabriel and Shahabi, Cyrus},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {5},
        pages = {1066--1078},
        doi = {10.14778/3510397.3510404},
        url = {https://doi.org/10.14778/3510397.3510404},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,883	LDPTrace: Locally Differentially Private Trajectory Synthesis	2023	VLDB	5.9587932e-05
6,335	A Neural Approach to Spatio-Temporal Data Release with User-Level Differential Privacy	2023	SIGMOD	5.8100198e-05
9,209	NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks	2023	SIGMOD	5.2061781e-05
9,345	DP-starJ: A Differential Private Scheme towards Analytical Star-Join Queries	2023	SIGMOD	5.1901916e-05
9,473	PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy	2024	VLDB	5.1708619e-05
10,819	PrivSTD: Differentially Private Spatio-temporal Trajectory Density Data Publication	2026	VLDB	4.9793485e-05
11,885	Fast Dataset Search with Earth Mover's Distance	2022	VLDB	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
121	Boosting the Accuracy of Differentially Private Histograms Through Consistency	2010	VLDB	0.00031089378
318	DeepDB: Learn from Data, not from Queries!	2020	VLDB	0.00021167555
371	STHoles: A Multidimensional Workload-Aware Histogram	2001	SIGMOD	0.00019829769
558	Understanding Hierarchical Methods for Differentially Private Histograms	2013	VLDB	0.00016470707
800	Differentially Private Data Cubes: Optimizing Noise Sources and Consistency	2011	SIGMOD	0.00013875702
1,324	PrivTree: A Differentially Private Algorithm for Hierarchical Decompositions	2016	SIGMOD	0.00011023355
1,528	A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy	2014	VLDB	0.00010349919
1,829	DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models	2019	SIGMOD	9.5510333e-05
2,056	Understanding the Sparse Vector Technique for Differential Privacy	2017	VLDB	9.111259e-05
2,090	Optimizing error of high-dimensional statistical queries under differential privacy	2018	VLDB	9.0657103e-05
2,298	Principled Evaluation of Differentially Private Algorithms using DPBench	2016	SIGMOD	8.6731734e-05
3,067	Oracle AutoML: A Fast and Predictive AutoML Pipeline	2020	VLDB	7.6876681e-05
3,711	Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics	2017	SIGMOD	7.0783969e-05

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8	3,148	Private Queries in Location Based Services: Anonymizers are not Necessary	2008	SIGMOD
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