Counterfactual Explanation at Will, with Zero Privacy Leakage

Summary: CPC: client-side, data-driven counterfactual explanations that work even without model-owner cooperation, restoring user control over the right-to-explain. Key novelty: formal zero-privacy-leakage guarantee against model extraction, with complexity analysis plus fast, high-quality algorithms. (summarized by gpt-5.4-mini on May 24 2026)

Paper ID: h8288bb7adb70d4f8
Venue: SIGMOD
Year: 2024
Pagerank: 4.9605343e-05
Overall Rank: 11,571 | 22.44%
DOI: 10.1145/3654933
PDF: Download (CC BY 4.0)

Incoming Non-self Citations Over Time

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Authors

1. Shuai An (University of Edinburgh)
2. Yang Cao (University of Edinburgh)

BibTeX Citation

@inproceedings{an_sigmod24,
        title = {{Counterfactual Explanation at Will, with Zero Privacy Leakage}},
        author = {An, Shuai and Cao, Yang},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3654933},
        url = {https://dl.acm.org/doi/10.1145/3654933},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 27 of 27 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
17	Provenance Semirings	2007	PODS	0.00059660827
191	Scorpion: Explaining Away Outliers in Aggregate Queries	2013	VLDB	0.0002578784
581	The Complexity of Causality and Responsibility for Query Answers and non-Answers	2011	VLDB	0.00016042765
672	A Formal Approach to Finding Explanations for Database Queries	2014	SIGMOD	0.00014903109
879	Interpretable and Informative Explanations of Outcomes	2015	VLDB	0.00013255435
1,949	Max-Sum Diversification, Monotone Submodular Functions and Dynamic Updates	2012	PODS	9.3036077e-05
1,954	Interpretable Data-Based Explanations for Fairness Debugging	2022	SIGMOD	9.2965173e-05
1,989	Causality and Explanations in Databases	2014	VLDB	9.2277193e-05
2,233	Explaining Query Answers with Explanation-Ready Databases	2016	VLDB	8.7844607e-05
2,459	Tracing Data Errors with View-Conditioned Causality	2011	SIGMOD	8.4137923e-05
3,074	Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals	2021	SIGMOD	7.6622293e-05
4,299	Towards Tight Bounds for the Streaming Set Cover Problem	2016	PODS	6.6638133e-05
4,577	HYPER: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach	2022	SIGMOD	6.5111757e-05
4,752	Interactive Summarization and Exploration of Top Aggregate Query Answers	2018	VLDB	6.4226993e-05
4,865	High-Level Why-Not Explanations using Ontologies	2015	PODS	6.3619008e-05
5,201	Explainable AI: Foundations, Applications, Opportunities for Data Management Research	2022	SIGMOD	6.2175939e-05
6,196	Causal Data Integration	2023	VLDB	5.8366172e-05
6,496	HypDB: A Demonstration of Detecting, Explaining and Resolving Bias in OLAP queries	2018	VLDB	5.7489341e-05
6,502	Approximate Summaries for Why and Why-not Provenance	2020	VLDB	5.7468661e-05
6,608	Explain3D: Explaining Disagreements in Disjoint Datasets	2019	VLDB	5.7187078e-05
6,982	Scalable Package Queries in Relational Database Systems	2016	VLDB	5.6121014e-05
7,194	DataPrism: Exposing Disconnect between Data and Systems	2022	SIGMOD	5.573413e-05
7,633	BugDoc: Algorithms to Debug Computational Processes	2020	SIGMOD	5.4635757e-05
8,152	Scaling Package Queries to a Billion Tuples via Hierarchical Partitioning and Customized Optimization	2024	VLDB	5.3735878e-05
8,540	Causality-Guided Adaptive Interventional Debugging	2020	SIGMOD	5.3042872e-05
10,210	sPaQLTooLs: A Stochastic Package Query Interface for Scalable Constrained Optimization	2020	VLDB	5.0491152e-05
11,561	Relative Keys: Putting Feature Explanation into Context	2024	SIGMOD	4.9605343e-05

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