Demonstration of DPClustX: Differentially Private Explanations for Clusters
Summary: DPClustX offers DP, histogram-based explanations for black-box clustering with attribute selection for compact, privacy-aware histograms. An integrated LLM plugin adds natural-language explanations; the Python package supports any DP clustering algorithm. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Amir Gilad (Hebrew University)
- 2. Tova Milo (Tel Aviv University)
- 3. Kathy Razmadze (Tel Aviv University)
- 4. Ron Zadicario (Tel Aviv University)
BibTeX Citation
@inproceedings{gilad_sigmod25,
title = {{Demonstration of DPClustX: Differentially Private Explanations for Clusters}},
author = {Gilad, Amir and Milo, Tova and Razmadze, Kathy and Zadicario, Ron},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3725102},
url = {https://dl.acm.org/doi/10.1145/3722212.3725102},
year = {2025}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,184 | FEDEX: An Explainability Framework for Data Exploration Steps | 2022 | VLDB | 5.4709725e-05 |
| 8,888 | TabEE: Tabular Embeddings Explanations | 2024 | SIGMOD | 5.3512451e-05 |
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