DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data

Summary: DiffPrep introduces differentiable bi-level search for preprocessing pipelines, enabling optimization in a continuous space. Continuous relaxation enables descent to find pipelines with a single training, yielding up to 6.6pp gains on 15/18 datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6748
Venue: SIGMOD
Year: 2023
Pagerank: 6.2801343e-05
Overall Rank: 5,291 | 63.70%
DOI: 10.1145/3589328

Incoming Non-self Citations Over Time

Authors

1. Peng Li (Georgia Institute of Technology)
2. Zhiyi Chen (Georgia Institute of Technology)
3. Xu Chu (Georgia Institute of Technology)
4. Kexin Rong (Georgia Institute of Technology)

BibTeX Citation

@inproceedings{li_sigmod23,
        title = {{DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data}},
        author = {Li, Peng and Chen, Zhiyi and Chu, Xu and Rong, Kexin},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3589328},
        url = {https://dl.acm.org/doi/10.1145/3589328},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,914	CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning	2024	SIGMOD	5.3483178e-05
10,303	Understanding the Impact of Data Noise in Federated Learning: [Experiments & Analysis]	2026	SIGMOD	5.093636e-05
10,614	LLM-AutoDP: Automatic Data Processing via LLM Agents for Model Fine-tuning	2026	VLDB	5.093636e-05
10,991	Stress-Testing ML Pipelines with Adversarial Data Corruption	2025	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
582	ActiveClean: Interactive Data Cleaning For Statistical Modeling	2016	VLDB	0.00016148948
1,004	Democratizing Data Science through Interactive Curation of ML Pipelines	2019	SIGMOD	0.00012701932
1,323	Data Cleaning: Overview and Emerging Challenges	2016	SIGMOD	0.00011152602
1,351	Detecting Data Errors: Where are we and what needs to be done?	2016	VLDB	0.00011064851
1,402	Creating Embeddings of Heterogeneous Relational Datasets for Data Integration Tasks	2020	SIGMOD	0.00010888094
2,147	Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions	2021	VLDB	9.0831495e-05
4,735	Leva: Boosting Machine Learning Performance with Relational Embedding Data Augmentation	2022	SIGMOD	6.5315782e-05

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