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APEx: Accuracy-Aware Differentially Private Data Exploration

Summary: APEx enables accuracy-aware, DP-driven data exploration with adaptive queries and accuracy bounds. It translates queries and bounds into DP algorithms with low privacy loss, guaranteeing accuracy and end-to-end DP proofs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5623
Venue
SIGMOD
Year
2019
Pagerank
5.2291685e-05
Overall Rank
6,065 | 57.81%
DOI
10.1145/3299869.3300092

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 13 of 13 citing papers.

Rank Citing Paper Year Venue Pagerank
2,806 CryptEpsilon: Crypto-Assisted Differential Privacy on Untrusted Servers 2020 SIGMOD 8.0911177e-05
3,831 Kamino: Constraint-Aware Differentially Private Data Synthesis 2021 VLDB 6.7181688e-05
7,417 DProvDB: Differentially Private Query Processing with Multi-Analyst Provenance 2023 SIGMOD 4.7355114e-05
7,485 Differentially Private Data Generation with Missing Data 2024 VLDB 4.7180617e-05
8,837 Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration 2023 VLDB 4.4393184e-05
9,512 Answering Private Linear Queries Adaptively using the Common Mechanism 2023 VLDB 4.3335882e-05
9,514 Framework for Differentially Private Data Analysis with Multiple Accuracy Requirements 2021 SIGMOD 4.3335882e-05
9,592 HDPView: Differentially Private Materialized View for Exploring High Dimensional Relational Data 2022 VLDB 4.3202988e-05
9,697 PCOR: Private Contextual Outlier Release via Differentially Private Search 2021 SIGMOD 4.3022295e-05
10,015 Differentially Private Explanations for Clusters 2026 SIGMOD 4.1945683e-05
11,032 SWAT: A System-Wide Approach to Tunable Leakage Mitigation in Encrypted Data Stores 2024 VLDB 4.1945683e-05
11,382 MIDE: Accuracy Aware Minimally Invasive Data Exploration For Decision Support 2022 VLDB 4.1945683e-05
11,527 Catch a Blowfish Alive: A Demonstration of Policy-Aware Differential Privacy for Interactive Data Exploration 2021 VLDB 4.1945683e-05
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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
83 Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis 2009 SIGMOD 0.00053933811
489 Data Curation at Scale: The Data Tamer System 2013 CIDR 0.00022030728
712 Magellan: Toward Building Entity Matching Management Systems 2016 VLDB 0.00017732426
742 Optimizing Linear Counting Queries Under Differential Privacy 2010 PODS 0.00017360873
1,567 PrivBasis: Frequent Itemset Mining with Differential Privacy 2012 VLDB 0.0001133268
1,602 Calibrating Data to Sensitivity in Private Data Analysis: A Platform for Differentially-Private Analysis of Weighted Datasets 2014 VLDB 0.00011199166
1,935 A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy 2014 VLDB 0.00010032967
2,434 Optimizing error of high-dimensional statistical queries under differential privacy 2018 VLDB 8.8278955e-05
2,465 Principled Evaluation of Differentially Private Algorithms using DPBench 2016 SIGMOD 8.7518123e-05
2,685 On Differentially Private Frequent Itemset Mining 2013 VLDB 8.3070708e-05
4,502 ϵktelo: A Framework for Defining Differentially-Private Computations 2018 SIGMOD 6.1366984e-05
4,668 PrivateClean: Data Cleaning and Differential Privacy 2016 SIGMOD 6.0115918e-05
5,246 Utility Cost of Formal Privacy for Releasing National Employer-Employee Statistics 2017 SIGMOD 5.6063332e-05
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Semantically Similar Papers

Overall Rank Paper Year Venue Pagerank
1,935 A Data- and Workload-Aware Algorithm for Range Queries Under Differential Privacy 2014 VLDB 0.00010032967
83 Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis 2009 SIGMOD 0.00053933811
10,015 Differentially Private Explanations for Clusters 2026 SIGMOD 4.1945683e-05
9,514 Framework for Differentially Private Data Analysis with Multiple Accuracy Requirements 2021 SIGMOD 4.3335882e-05
453 Towards Practical Differential Privacy for SQL Queries 2018 VLDB 0.00022741848
1,738 PrivateSQL: A Differentially Private SQL Query Engine 2019 VLDB 0.00010720057
2,274 An Adaptive Mechanism for Accurate Query Answering under Differential Privacy 2012 VLDB 9.1297703e-05
11,281 Explaining Differentially Private Query Results With DPXPlain 2023 VLDB 4.1945683e-05
9,766 DPXPlain: Privately Explaining Aggregate Query Answers 2023 VLDB 4.2856106e-05
8,837 Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration 2023 VLDB 4.4393184e-05