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Outliers: The Good, the Bad and the Ugly

Summary: Distinguishes good (novel), bad (errors), and ugly (feature‑influential errors) outliers and shows only ugly ones harm ML classifier accuracy. Proposes OMRs—predicate rules combining outlier detectors and statistics—to learn and repair ugly outliers (not delete), boosting accuracy 7.2% on average, up to 34.8%. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
hb546dee9075a9212
Venue
SIGMOD
Year
2026
Pagerank
4.9793485e-05
Overall Rank
10,530 | 29.21%
DOI
10.1145/3749177

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{chen_sigmod26,
        title = {{Outliers: The Good, the Bad and the Ugly}},
        author = {Chen, Shenglin and Fan, Wenfei and Jin, Ruochun},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3749177},
        url = {https://dl.acm.org/doi/10.1145/3749177},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
10,500 Shielding PII to Prevent Re-identification and Preserve Utility 2026 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 23 of 23 cited papers.

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

Rank Cited Paper Year Venue Pagerank
33 Consistent Query Answers in Inconsistent Databases 1999 PODS 0.00049349003
142 LOF: Identifying Density-Based Local Outliers 2000 SIGMOD 0.00029202746
164 Mining Frequent Patterns without Candidate Generation 2000 SIGMOD 0.00027412227
350 Discovering Denial Constraints 2013 VLDB 0.00020253521
483 ActiveClean: Interactive Data Cleaning For Statistical Modeling 2016 VLDB 0.00017590977
603 A Hybrid Approach to Functional Dependency Discovery 2016 SIGMOD 0.00015699254
695 Algorithms for Mining Distance-Based Outliers in Large Datasets 1998 VLDB 0.00014702685
878 Interpretable and Informative Explanations of Outcomes 2015 VLDB 0.00013302631
1,031 On Generating Near-Optimal Tableaux for Conditional Functional Dependencies 2008 VLDB 0.00012405065
1,971 Discovery of Approximate (and Exact) Denial Constraints 2020 VLDB 9.2873596e-05
4,103 AutoOD: Automatic Outlier Detection 2023 SIGMOD 6.8066074e-05
4,233 The Interaction between Functional Dependencies and Template Dependencies 1980 SIGMOD 6.7136317e-05
5,151 CAPE: Explaining Outliers by Counterbalancing 2019 VLDB 6.2528145e-05
6,775 Missing Data Imputation with Uncertainty-Driven Network 2024 SIGMOD 5.685295e-05
7,042 Human-in-the-loop Outlier Detection 2020 SIGMOD 5.6142998e-05
7,872 Rock: Cleaning Data by Embedding ML in Logic Rules 2024 SIGMOD 5.4362062e-05
7,876 CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties 2021 VLDB 5.4348457e-05
7,912 CoCo: Interactive Exploration of Conformance Constraints for Data Understanding and Data Cleaning 2021 SIGMOD 5.4279818e-05
7,924 Outlier Summarization via Human Interpretable Rules 2024 VLDB 5.425954e-05
8,528 A Demonstration of KGLac: A Data Discovery and Enrichment Platform for Data Science 2021 VLDB 5.3225503e-05
9,511 ActiveDeeper: A Model-based Active Data Enrichment System 2020 VLDB 5.1701756e-05
10,339 Parallel Rule Discovery from Large Datasets by Sampling 2022 SIGMOD 5.0195045e-05
11,724 Enriching Recommendation Models with Logic Conditions 2023 SIGMOD 4.9793485e-05
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