CAPE: Explaining Outliers by Counterbalancing
Summary: Explains surprising aggregation outcomes by counterbalancing with opposite-direction outliers. Defines coarse aggregate regression patterns (ARPs) and presents an efficient algorithm to surface counterbalances as explanations. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhengjie Miao (Duke University)
- 2. Qitian Zeng (Illinois Institute of Technology)
- 3. Chenjie Li (Illinois Institute of Technology)
- 4. Boris Glavic (Illinois Institute of Technology)
- 5. Oliver Kennedy (State University of New York at Buffalo)
- 6. Sudeepa Roy (Duke University)
BibTeX Citation
@article{miao_vldb19,
title = {{CAPE: Explaining Outliers by Counterbalancing}},
author = {Miao, Zhengjie and Zeng, Qitian and Li, Chenjie and Glavic, Boris and Kennedy, Oliver and Roy, Sudeepa},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {12},
pages = {1806--1809},
doi = {10.14778/3352063.3352071},
url = {https://doi.org/10.14778/3352063.3352071},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,660 | Banzhaf Values for Facts in Query Answering | 2024 | SIGMOD | 6.1305635e-05 |
| 6,576 | Toward Interpretable and Actionable Data Analysis with Explanations and Causality | 2022 | VLDB | 5.8364729e-05 |
| 8,802 | Outlier Summarization via Human Interpretable Rules | 2024 | VLDB | 5.3685765e-05 |
| 9,831 | ExTuNe: Explaining Tuple Non-conformance | 2020 | SIGMOD | 5.2125702e-05 |
| 10,324 | Outliers: The Good, the Bad and the Ugly | 2026 | SIGMOD | 5.093636e-05 |
| 10,557 | Database Views as Explanations for Relational Deep Learning | 2026 | VLDB | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 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 | 0.00059843817 |
| 191 | Scorpion: Explaining Away Outliers in Aggregate Queries | 2013 | VLDB | 0.00026096009 |
| 663 | A Formal Approach to Finding Explanations for Database Queries | 2014 | SIGMOD | 0.00015174751 |
| 4,638 | Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances | 2019 | SIGMOD | 6.5919801e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 3,958 | Continuous Outlier Detection in Data Streams: An Extensible Framework and State-Of-The-Art Algorithms | 2013 | SIGMOD |
| 2 | 9,842 | CaJaDE: Explaining Query Results by Augmenting Provenance with Context | 2022 | VLDB |
| 3 | 11,480 | Explaining Differentially Private Query Results With DPXPlain | 2023 | VLDB |
| 4 | 9,269 | A Dynamically Adaptive Distributed System for Processing Complex Continuous Queries | 2005 | VLDB |
| 5 | 8,852 | LensXPlain: Visualizing and Explaining Contributing Subsets for Aggregate Query Answers | 2019 | VLDB |
| 6 | 3,031 | Interactive Outlier Exploration in Big Data Streams | 2014 | VLDB |
| 7 | 9,543 | OIE: An Interpretable System for Outlier Explanation and Summarization | 2025 | SIGMOD |
| 8 | 8,139 | CAPE: Continuous Query Engine with Heterogeneous-Grained Adaptivity | 2004 | VLDB |
| 9 | 191 | Scorpion: Explaining Away Outliers in Aggregate Queries | 2013 | VLDB |
| 10 | 4,638 | Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances | 2019 | SIGMOD |