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Distributed Outlier Detection using Compressive Sensing

Summary: Distributed outlier detection via compressive sensing; data sketches reduce inter-node communication to log N. Handles sparse data and data concentrated around an unknown value; implemented in Hadoop on real web-scale logs; up to 99% I/O reduction and up to 40% faster end-to-end queries. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5098
Venue
SIGMOD
Year
2015
Pagerank
5.5429229e-05
Overall Rank
7,795 | 46.52%
DOI
10.1145/2723372.2747641

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{yan_sigmod15,
        title = {{Distributed Outlier Detection using Compressive Sensing}},
        author = {Yan, Ying and Zhang, Jiaxing and Huang, Bojun and Sun, Xuzhan and Mu, Jiaqi and Zhang, Zheng and Moscibroda, Thomas},
        series = {{SIGMOD} '15},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2723372.2747641},
        url = {https://dl.acm.org/doi/10.1145/2723372.2747641},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
8,653 Bias-Aware Sketches 2017 VLDB 5.3914428e-05
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Outgoing Citations (Sorted by Pagerank)

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