Cleaning Crowdsourced Labels Using Oracles for Statistical Classification
Summary: Oracle-based label cleaning for crowdsourced data in classification. TARS estimates test performance from noisy labels with confidence bounds and selects which labels to clean to boost training accuracy under budget, beating existing strategies. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mohamad Dolatshah (Simon Fraser University)
- 2. Mathew Teoh (Simon Fraser University)
- 3. Jiannan Wang (Simon Fraser University)
- 4. Jian Pei (JD Group; Simon Fraser University)
BibTeX Citation
@article{dolatshah_vldb19,
title = {{Cleaning Crowdsourced Labels Using Oracles for Statistical Classification}},
author = {Dolatshah, Mohamad and Teoh, Mathew and Wang, Jiannan and Pei, Jian},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {4},
pages = {376--389},
doi = {10.14778/3297753.3297758},
url = {https://doi.org/10.14778/3297753.3297758},
year = {2019}
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