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ActiveClean: Interactive Data Cleaning For Statistical Modeling

Summary: ActiveClean enables progressive, iterative cleaning during convex-loss model training while preserving convergence guarantees. It prioritizes records most likely to affect model parameters, achieving substantially higher accuracy than uniform sampling and active learning under fixed cleaning budgets. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11569
Venue
VLDB
Year
2016
Pagerank
0.00016148948
Overall Rank
582 | 96.01%
DOI
10.14778/2994509.2994511

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{krishnan_vldb16,
        title = {{ActiveClean: Interactive Data Cleaning For Statistical Modeling}},
        author = {Krishnan, Sanjay and Wang, Jiannan and Wu, Eugene and Franklin, Michael J. and Goldberg, Ken},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {12},
        pages = {948--959},
        doi = {10.14778/2994509.2994511},
        url = {https://doi.org/10.14778/2994509.2994511},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 48 of 48 citing papers.

Rank Citing Paper Year Venue Pagerank
1,147 Data Management Challenges in Production Machine Learning 2017 SIGMOD 0.00011974846
1,250 Data Management in Machine Learning: Challenges, Techniques, and Systems 2017 SIGMOD 0.00011485301
1,476 Baran: Effective Error Correction via a Unified Context Representation and Transfer Learning 2020 VLDB 0.00010659277
2,147 Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions 2021 VLDB 9.0831495e-05
2,297 Raha: A Configuration-Free Error Detection System 2019 SIGMOD 8.7897221e-05
2,584 Complaint-driven Training Data Debugging for Query 2.0 2020 SIGMOD 8.3783546e-05
2,888 AI Meets Database: AI4DB and DB4AI 2021 SIGMOD 7.9941489e-05
3,147 Auto-Detect: Data-Driven Error Detection in Tables 2018 SIGMOD 7.7077175e-05
3,272 VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition 2021 VLDB 7.5775321e-05
3,281 Cleaning Crowdsourced Labels Using Oracles for Statistical Classification 2019 VLDB 7.5706653e-05
3,361 Cleaning Denial Constraint Violations through Relaxation 2020 SIGMOD 7.4872032e-05
3,580 Automatic Data Repair: Are We Ready to Deploy? 2024 VLDB 7.2888516e-05
3,886 GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data 2023 SIGMOD 7.0460597e-05
4,100 Data Integration and Machine Learning: A Natural Synergy 2018 SIGMOD 6.9016092e-05
4,130 PrIU: A Provenance-Based Approach for Incrementally Updating Regression Models 2020 SIGMOD 6.8839621e-05
4,658 OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning 2021 SIGMOD 6.5817368e-05
4,966 Rotom: A Meta-Learned Data Augmentation Framework for Entity Matching, Data Cleaning, Text Classification, and Beyond 2021 SIGMOD 6.4225454e-05
5,131 Enabling SQL-based Training Data Debugging for Federated Learning 2022 VLDB 6.3537809e-05
5,291 DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data 2023 SIGMOD 6.2801343e-05
6,145 Equitable Data Valuation Meets the Right to Be Forgotten in Model Markets 2023 VLDB 5.9604471e-05
7,232 Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications 2023 SIGMOD 5.6659017e-05
7,395 Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines 2023 SIGMOD 5.6257796e-05
7,868 CHEF: A Cheap and Fast Pipeline for Iteratively Cleaning Label Uncertainties 2021 VLDB 5.5277527e-05
7,880 Learning Over Dirty Data Without Cleaning 2020 SIGMOD 5.5244204e-05
8,244 SHiFT: An Efficient, Flexible Search Engine for Transfer Learning 2023 VLDB 5.4587712e-05
8,594 Exploratory Training: When Annotators Learn About Data 2023 SIGMOD 5.4053095e-05
8,838 The Cost of Representation by Subset Repairs 2025 VLDB 5.3592132e-05
8,914 CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning 2024 SIGMOD 5.3483178e-05
9,193 Query-Guided Resolution in Uncertain Databases 2023 SIGMOD 5.3058708e-05
9,204 Selecting Data to Clean for Fact Checking: Minimizing Uncertainty vs. Maximizing Surprise 2019 VLDB 5.3058708e-05
9,245 Towards Observability for Production Machine Learning Pipelines 2022 VLDB 5.2992628e-05
9,381 Deduplicated Sampling On-Demand 2025 VLDB 5.2755515e-05
9,437 GIDCL: A Graph-Enhanced Interpretable Data Cleaning Framework with Large Language Models 2024 SIGMOD 5.2687567e-05
9,539 DataVinci: Learning Syntactic and Semantic String Repairs 2025 SIGMOD 5.2528121e-05
10,303 Understanding the Impact of Data Noise in Federated Learning: [Experiments & Analysis] 2026 SIGMOD 5.093636e-05
10,322 Minimum Change ≠ Best Cleaning: Parallel and Incremental Error Detection under Integrity Constraints 2026 SIGMOD 5.093636e-05
10,324 Outliers: The Good, the Bad and the Ugly 2026 SIGMOD 5.093636e-05
10,757 Data Enhancement for Binary Classification of Relational Data 2025 SIGMOD 5.093636e-05
10,800 Two Birds with One Stone: Efficient Deep Learning over Mislabeled Data through Subset Selection 2025 SIGMOD 5.093636e-05
10,882 CatDB: Data-catalog-guided, LLM-based Generation of Data-centric ML Pipelines 2025 VLDB 5.093636e-05
10,896 Still More Shades of Null: An Evaluation Suite for Responsible Missing Value Imputation 2025 VLDB 5.093636e-05
11,043 mlidea: Interactively Improving ML Data Preparation Code via “Shadow Pipelines” 2025 VLDB 5.093636e-05
11,169 Certain and Approximately Certain Models for Statistical Learning 2024 SIGMOD 5.093636e-05
11,260 Efficiently Mitigating the Impact of Data Drift on Machine Learning Pipelines 2024 VLDB 5.093636e-05
11,343 Generalizable Data Cleaning of Tabular Data in Latent Space 2024 VLDB 5.093636e-05
11,384 LinCQA: Faster Consistent Query Answering with Linear Time Guarantees 2023 SIGMOD 5.093636e-05
11,629 Ease.ML: A Lifecycle Management System for MLDev and MLOps 2021 CIDR 5.093636e-05
11,877 IHCS: An Integrated Hybrid Cleaning System 2019 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 9 of 9 cited papers.

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

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