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Interpretable and Informative Explanations of Outcomes

Summary: Problem: multi-dimensional data with a binary outcome; build interpretable explanation tables that summarize which dimension-value combinations affect the outcome. Approach: sampling-based heuristics plus efficient information-content estimation, addressing hardness of optimal explanations and showing empirical gains over related methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11360
Venue
VLDB
Year
2015
Pagerank
0.0001356511
Overall Rank
858 | 94.12%
DOI
10.14778/2735461.2735467

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{gebaly_vldb15,
        title = {{Interpretable and Informative Explanations of Outcomes}},
        author = {Gebaly, Kareem El and Agrawal, Parag and Golab, Lukasz and Korn, Flip and Srivastava, Divesh},
        journal = {PVLDB},
        series = {{VLDB} '15},
        volume = {8},
        number = {1},
        pages = {61--72},
        doi = {10.14778/2735461.2735467},
        url = {https://doi.org/10.14778/2735461.2735467},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 38 of 38 citing papers.

Rank Citing Paper Year Venue Pagerank
1,534 Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series 2021 VLDB 0.00010464308
1,756 SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle 2020 CIDR 9.8172465e-05
1,792 MacroBase: Prioritizing Attention in Fast Data 2017 SIGMOD 9.7436856e-05
2,273 SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging 2021 SIGMOD 8.8230899e-05
2,759 Data X-Ray: A Diagnostic Tool for Data Errors 2015 SIGMOD 8.1577506e-05
4,638 Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances 2019 SIGMOD 6.5919801e-05
4,990 Explaining Dataset Changes for Semantic Data Versioning with Explain-Da-V 2023 VLDB 6.4105738e-05
5,396 Putting Things into Context: Rich Explanations for Query Answers using Join Graphs 2021 SIGMOD 6.2329373e-05
6,360 Approximate Summaries for Why and Why-not Provenance 2020 VLDB 5.9009081e-05
6,576 Toward Interpretable and Actionable Data Analysis with Explanations and Causality 2022 VLDB 5.8364729e-05
6,759 REDS: Rule Extraction for Discovering Scenarios 2021 SIGMOD 5.7827401e-05
6,763 Smart Drill-Down: A New Data Exploration Operator 2015 VLDB 5.7810308e-05
6,932 Summarized Causal Explanations For Aggregate Views 2024 SIGMOD 5.7362362e-05
7,003 Guided Exploration of Data Summaries 2022 VLDB 5.7278883e-05
7,068 DataPrism: Exposing Disconnect between Data and Systems 2022 SIGMOD 5.7119157e-05
8,153 The Cascading Analysts Algorithm 2018 SIGMOD 5.4769543e-05
8,185 BugDoc: Algorithms to Debug Computational Processes 2020 SIGMOD 5.4707797e-05
8,583 Query Log Compression for Workload Analytics 2019 VLDB 5.4079618e-05
8,719 DPXPlain: Privately Explaining Aggregate Query Answers 2023 VLDB 5.3774243e-05
8,802 Outlier Summarization via Human Interpretable Rules 2024 VLDB 5.3685765e-05
8,889 Provenance-based Data Skipping 2022 VLDB 5.3512428e-05
9,045 Causality-Guided Adaptive Interventional Debugging 2020 SIGMOD 5.3252192e-05
9,418 BugDoc: A System for Debugging Computational Pipelines 2020 SIGMOD 5.2732157e-05
9,773 Fair and Actionable Causal Prescription Ruleset 2025 SIGMOD 5.2209769e-05
9,842 CaJaDE: Explaining Query Results by Augmenting Provenance with Context 2022 VLDB 5.210037e-05
10,324 Outliers: The Good, the Bad and the Ugly 2026 SIGMOD 5.093636e-05
10,436 Causal Explanations for Disparate Trends: Where and Why? 2026 SIGMOD 5.093636e-05
10,441 Data-Semantics-Aware Recommendation of Diverse Pivot Tables 2026 SIGMOD 5.093636e-05
10,502 Stress-Testing Causal Claims via Cardinality Repairs 2026 SIGMOD 5.093636e-05
10,557 Database Views as Explanations for Relational Deep Learning 2026 VLDB 5.093636e-05
10,710 CauSumX: Summarized Causal Explanations For Group-By-Average Queries 2025 SIGMOD 5.093636e-05
10,979 Finding Convincing Views to Endorse a Claim 2025 VLDB 5.093636e-05
11,157 Relative Keys: Putting Feature Explanation into Context 2024 SIGMOD 5.093636e-05
11,170 Counterfactual Explanation at Will, with Zero Privacy Leakage 2024 SIGMOD 5.093636e-05
11,260 Efficiently Mitigating the Impact of Data Drift on Machine Learning Pipelines 2024 VLDB 5.093636e-05
11,480 Explaining Differentially Private Query Results With DPXPlain 2023 VLDB 5.093636e-05
11,672 Exploring Ratings in Subjective Databases 2021 SIGMOD 5.093636e-05
11,938 Provenance Summaries for Answers and Non-Answers 2018 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

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