Active Reinforcement Learning for Data Preparation: Learn2Clean with Human-In-The-Loop
Summary: Introduces Learn2Clean: a human-in-the-loop active reinforcement learning method that incrementally explores and prunes the combinatorial space of data-cleaning and preprocessing pipelines by querying users to guide actions for a target ML task. Frames data preparation as AI-hard, leveraging human feedback to trade off evaluation cost and downstream model quality, contrasting with passive AutoML/bandit approaches. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Laure Berti-Equille (Aix-Marseille University; Institut de Recherche pour le Développement; National Centre for Scientific Research; University of Toulon)
BibTeX Citation
@inproceedings{bertiequille_cidr20,
address = {Amsterdam, Netherlands},
series = {{CIDR} '20},
title = {{Active Reinforcement Learning for Data Preparation: Learn2Clean with Human-In-The-Loop}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Berti-Equille, Laure},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,004 | Democratizing Data Science through Interactive Curation of ML Pipelines | 2019 | SIGMOD | 0.00012701932 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 6,074 | Automatic Data Acquisition for Deep Learning | 2021 | VLDB |
| 2 | 1,323 | Data Cleaning: Overview and Emerging Challenges | 2016 | SIGMOD |
| 3 | 5,835 | Semi-Supervised Data Cleaning with Raha and Baran | 2021 | CIDR |
| 4 | 11,038 | DemandClean: A Multi-Objective Learning Framework for Balancing Model Tolerance to Data Authenticity and Diversity | 2025 | VLDB |
| 5 | 4,875 | Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search | 2021 | VLDB |
| 6 | 8,914 | CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning | 2024 | SIGMOD |
| 7 | 13,435 | Data Cleaning in the Era of Data Science: Challenges and Opportunities | 2021 | CIDR |
| 8 | 5,794 | ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning | 2016 | SIGMOD |
| 9 | 8,177 | HAIPipe: Combining Human-generated and Machine-generated Pipelines for Data Preparation | 2023 | SIGMOD |
| 10 | 1,004 | Democratizing Data Science through Interactive Curation of ML Pipelines | 2019 | SIGMOD |