Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration

Summary: CacheDP: an interactive, accuracy-aware DP query engine that maintains a differentially private cache of past answers to reuse for new workloads, reducing incremental privacy cost while meeting per-query accuracy guarantees. Novel cache-aware DP cost optimization that integrates complex DP mechanisms with the structured cache to minimize cumulative privacy loss. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13501
Venue: VLDB
Year: 2023
Pagerank: 5.3589295e-05
Overall Rank: 8,843 | 39.33%
DOI: 10.14778/3574245.3574246

Incoming Non-self Citations Over Time

Authors

1. Miti Mazmudar (University of Waterloo)
2. Thomas Humphries (University of Waterloo)
3. Jiaxiang Liu (University of Waterloo)
4. Matthew Rafuse (University of Waterloo)
5. Xi He (University of Waterloo)

BibTeX Citation

@article{mazmudar_vldb23,
        title = {{Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration}},
        author = {Mazmudar, Miti and Humphries, Thomas and Liu, Jiaxiang and Rafuse, Matthew and He, Xi},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {4},
        pages = {574--586},
        doi = {10.14778/3574245.3574246},
        url = {https://doi.org/10.14778/3574245.3574246},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
6,376	DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance	2023	SIGMOD	5.893174e-05
10,914	Calibrating Noise for Group Privacy in Subsampled Mechanisms	2025	VLDB	5.093636e-05
11,084	Exploring Exploratory Querying	2025	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
62	Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis	2009	SIGMOD	0.00038970535
121	Boosting the Accuracy of Differentially Private Histograms Through Consistency	2010	VLDB	0.00031639377
281	Towards Practical Differential Privacy for SQL Queries	2018	VLDB	0.00022445849
567	Understanding Hierarchical Methods for Differentially Private Histograms	2013	VLDB	0.00016420715
1,144	PrivateSQL: A Differentially Private SQL Query Engine	2019	VLDB	0.00011999046
1,308	PrivTree: A Differentially Private Algorithm for Hierarchical Decompositions	2016	SIGMOD	0.00011216361
1,767	IDEBench: A Benchmark for Interactive Data Exploration	2020	SIGMOD	9.805856e-05
1,906	GUPT: Privacy Preserving Data Analysis Made Easy	2012	SIGMOD	9.5020196e-05
3,412	Kamino: Constraint-Aware Differentially Private Data Synthesis	2021	VLDB	7.4344343e-05
5,055	APEx: Accuracy-Aware Differentially Private Data Exploration	2019	SIGMOD	6.3824509e-05
7,968	Optimizing Fitness-For-Use of Differentially Private Linear Queries	2021	VLDB	5.516666e-05

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4	1,144	PrivateSQL: A Differentially Private SQL Query Engine	2019	VLDB
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7	11,480	Explaining Differentially Private Query Results With DPXPlain	2023	VLDB
8	7,147	Architecting a Differentially Private SQL Engine	2019	CIDR
9	8,719	DPXPlain: Privately Explaining Aggregate Query Answers	2023	VLDB
10	5,055	APEx: Accuracy-Aware Differentially Private Data Exploration	2019	SIGMOD