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 |
|---|---|---|---|---|
| 975 | Democratizing Data Science through Interactive Curation of ML Pipelines | 2019 | SIGMOD | 0.00012750518 |
Previous
Page 1 / 1
Next