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Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series Clustering

Summary: Chiaroscuro proposes Diptych, a privacy-preserving method enabling encrypted, DP-based collaboration for time-series clustering. Distributed on-device execution tolerates churn, delivering high clustering quality with DP and validated on real/synthetic data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5132
Venue
SIGMOD
Year
2015
Pagerank
5.093636e-05
Overall Rank
12,123 | 16.83%
DOI
10.1145/2723372.2749453

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Authors

BibTeX Citation

@inproceedings{allard_sigmod15,
        title = {{Chiaroscuro: Transparency and Privacy for Massive Personal Time-Series Clustering}},
        author = {Allard, Tristan and Hébrail, Georges and Masseglia, Florent and Pacitti, Esther},
        series = {{SIGMOD} '15},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2723372.2749453},
        url = {https://dl.acm.org/doi/10.1145/2723372.2749453},
        year = {2015}
}

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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
757 Differentially Private Aggregation of Distributed Time-Series with Transformation and Encryption 2010 SIGMOD 0.00014306168
12,460 Secure Personal Data Servers: a Vision Paper 2010 VLDB 5.093636e-05
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