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: 4.9769913e-05
Overall Rank: 11,521 | 22.57%
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	0.00059813669
190	Scorpion: Explaining Away Outliers in Aggregate Queries	2013	VLDB	0.0002582857
578	The Complexity of Causality and Responsibility for Query Answers and non-Answers	2011	VLDB	0.00016093679
671	A Formal Approach to Finding Explanations for Database Queries	2014	SIGMOD	0.00014948069
878	Interpretable and Informative Explanations of Outcomes	2015	VLDB	0.00013296412
1,937	Max-Sum Diversification, Monotone Submodular Functions and Dynamic Updates	2012	PODS	9.334308e-05
1,943	Interpretable Data-Based Explanations for Fairness Debugging	2022	SIGMOD	9.3254131e-05
1,983	Causality and Explanations in Databases	2014	VLDB	9.2548712e-05
2,222	Explaining Query Answers with Explanation-Ready Databases	2016	VLDB	8.8106741e-05
2,458	Tracing Data Errors with View-Conditioned Causality	2011	SIGMOD	8.4334752e-05
3,065	Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals	2021	SIGMOD	7.6876494e-05
4,285	Towards Tight Bounds for the Streaming Set Cover Problem	2016	PODS	6.68592e-05
4,568	HYPER: Hypothetical Reasoning With What-If and How-To Queries Using a Probabilistic Causal Approach	2022	SIGMOD	6.5279657e-05
4,731	Interactive Summarization and Exploration of Top Aggregate Query Answers	2018	VLDB	6.4440072e-05
4,842	High-Level Why-Not Explanations using Ontologies	2015	PODS	6.3828247e-05
5,179	Explainable AI: Foundations, Applications, Opportunities for Data Management Research	2022	SIGMOD	6.2382214e-05
6,186	Causal Data Integration	2023	VLDB	5.8559807e-05
6,488	Approximate Summaries for Why and Why-not Provenance	2020	VLDB	5.7659318e-05
6,492	HypDB: A Demonstration of Detecting, Explaining and Resolving Bias in OLAP queries	2018	VLDB	5.7647756e-05
6,602	Explain3D: Explaining Disagreements in Disjoint Datasets	2019	VLDB	5.7376131e-05
6,961	Scalable Package Queries in Relational Database Systems	2016	VLDB	5.63072e-05
7,185	DataPrism: Exposing Disconnect between Data and Systems	2022	SIGMOD	5.5890883e-05
7,632	BugDoc: Algorithms to Debug Computational Processes	2020	SIGMOD	5.4788866e-05
8,135	Scaling Package Queries to a Billion Tuples via Hierarchical Partitioning and Customized Optimization	2024	VLDB	5.3914151e-05
8,523	Causality-Guided Adaptive Interventional Debugging	2020	SIGMOD	5.3218847e-05
10,176	sPaQLTooLs: A Stochastic Package Query Interface for Scalable Constrained Optimization	2020	VLDB	5.0658661e-05
11,510	Relative Keys: Putting Feature Explanation into Context	2024	SIGMOD	4.9769913e-05

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