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Democratizing Data Science through Interactive Curation of ML Pipelines

Summary: Interactive AutoML for scientists via curated ML pipelines. Uses query-optimization, cost-based bandits, and Bayesian optimization to achieve interactive latency and beat expert solutions on unseen data across 300+ datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5737
Venue
SIGMOD
Year
2019
Pagerank
0.00012701932
Overall Rank
1,004 | 93.12%
DOI
10.1145/3299869.3319863

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{shang_sigmod19,
        title = {{Democratizing Data Science through Interactive Curation of ML Pipelines}},
        author = {Shang, Zeyuan and Zgraggen, Emanuel and Buratti, Benedetto and Kossmann, Ferdinand and Eichmann, Philipp and Chung, Yeounoh and Binnig, Carsten and Upfal, Eli and Kraska, Tim},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3319863},
        url = {https://dl.acm.org/doi/10.1145/3299869.3319863},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 27 of 27 citing papers.

Rank Citing Paper Year Venue Pagerank
1,121 ARDA: Automatic Relational Data Augmentation for Machine Learning 2020 VLDB 0.00012093059
1,447 Auctus: A Dataset Search Engine for Data Discovery and Augmentation 2021 VLDB 0.00010760327
1,756 SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle 2020 CIDR 9.8172465e-05
2,079 DBPal: A Fully Pluggable NL2SQL Training Pipeline 2020 SIGMOD 9.2060425e-05
4,062 AutoOD: Automatic Outlier Detection 2023 SIGMOD 6.9309994e-05
4,067 Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches 2021 VLDB 6.9293511e-05
4,240 LIMA: Fine-grained Lineage Tracing and Reuse in Machine Learning Systems 2021 SIGMOD 6.809685e-05
4,582 A Demonstration of AutoOD: A Self-Tuning Anomaly Detection System 2022 VLDB 6.6193306e-05
5,291 DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data 2023 SIGMOD 6.2801343e-05
5,498 SimpleTS: An Efficient and Universal Model Selection Framework for Time Series Forecasting 2023 VLDB 6.1972571e-05
5,699 Optimizing Machine Learning Workloads in Collaborative Environments 2020 SIGMOD 6.1170243e-05
5,839 Doing More with Less: Characterizing Dataset Downsampling for AutoML 2021 VLDB 6.0699037e-05
7,232 Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications 2023 SIGMOD 5.6659017e-05
7,473 The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development 2020 SIGMOD 5.609366e-05
7,687 ExDRa: Exploratory Data Science on Federated Raw Data 2021 SIGMOD 5.5671645e-05
8,050 Capturing and Querying Fine-grained Provenance of Preprocessing Pipelines in Data Science 2021 VLDB 5.5000099e-05
8,134 DORIAN in action: Assisted Design of Data Science Pipelines 2022 VLDB 5.4811783e-05
8,177 HAIPipe: Combining Human-generated and Machine-generated Pipelines for Data Preparation 2023 SIGMOD 5.4730821e-05
8,914 CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning 2024 SIGMOD 5.3483178e-05
9,290 Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale 2022 VLDB 5.2910774e-05
10,540 CAPS: Cost-Aware ML Pipeline Selection 2026 VLDB 5.093636e-05
10,827 A Systematic Study on Early Stopping Metrics in HPO and the Implications of Uncertainty 2025 VLDB 5.093636e-05
10,882 CatDB: Data-catalog-guided, LLM-based Generation of Data-centric ML Pipelines 2025 VLDB 5.093636e-05
10,931 AutoPrep: Natural Language Question-Aware Data Preparation with a Multi-Agent Framework 2025 VLDB 5.093636e-05
11,417 Demystifying the QoS and QoE of Edge-hosted Video Streaming Applications in the Wild with SNESet 2023 SIGMOD 5.093636e-05
11,674 Enforcing Constraints for Machine Learning Systems via Declarative Feature Selection: An Experimental Study 2021 SIGMOD 5.093636e-05
11,746 Active Reinforcement Learning for Data Preparation: Learn2Clean with Human-In-The-Loop 2020 CIDR 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 10 of 10 cited papers.

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

Rank Cited Paper Year Venue Pagerank
1 Access Path Selection in a Relational Database Management System 1979 SIGMOD 0.0024089429
288 Towards Estimation Error Guarantees for Distinct Values 2000 PODS 0.00022296371
532 MLbase: A Distributed Machine-learning System 2013 CIDR 0.00017072641
986 Effortless Data Exploration with zenvisage: An Expressive and Interactive Visual Analytics System 2017 VLDB 0.0001281777
1,392 Northstar: An Interactive Data Science System 2018 VLDB 0.00010936065
2,029 Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads 2018 VLDB 9.2843642e-05
2,050 Vizdom: Interactive Analytics through Pen and Touch 2015 VLDB 9.2546631e-05
2,059 LINVIEW: Incremental View Maintenance for Complex Analytical Queries 2014 SIGMOD 9.2471145e-05
5,084 Querying Without Keyboards 2013 CIDR 6.3692734e-05
6,693 GestureQuery: A Multitouch Database Query Interface 2013 VLDB 5.7992988e-05
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1 1,756 SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle 2020 CIDR
2 13,387 ML2DAC: Meta-learning to Democratize AutoML for Clustering Analyses 2023 SIGMOD
3 13,303 Demonstrating CatDB: LLM-based Generation of Data-centric ML Pipelines 2025 SIGMOD
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5 2,677 Explore-by-Example: An Automatic Query Steering Framework for Interactive Data Exploration 2014 SIGMOD
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