IDE: A System for Iterative Mislabel Detection-Reference-Cited by-同舟云学术

IDE: A System for Iterative Mislabel Detection

Published:2024-06-09 Issue: Volume: Page:500-503
ISSN:
Container-title:Companion of the 2024 International Conference on Management of Data
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Author:

Deng Yuhao¹^ORCID,Deng Qiyan¹^ORCID,Chai Chengliang¹^ORCID,Cao Lei²^ORCID,Tang Nan³^ORCID,Fan Ju⁴^ORCID,Wang Jiayi⁵^ORCID,Yuan Ye¹^ORCID,Wang Guoren¹^ORCID

Affiliation:

1. Beijing Institute of Technology, Beijing, China

2. University of Arizona & Massachusetts Institute of Technology, Tucson, USA

3. The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

4. Renmin University of China, Beijing, China

5. Tsinghua University, Beijng, China

Funder

NSFC

DITDP

the Beijing Natural Science Foundation

the Research Funds of Renmin University of China

the National Key R\&D Program of China

NSF (National Science Foundation)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626246.3654737

Reference7 articles.

1. AI Marques R Alejo J Badenas, JS Sanchez, and R Barandela. 2000. Decontamination of training data for supevised pattern recognition. Advances in Pattern Recognition Lecture Notes in Computer Science (2000).

2. Léon Bottou and Olivier Bousquet. 2007. The tradeoffs of large scale learning. Advances in neural information processing systems 20 (2007).

3. Yuhao Deng Chengliang Chai Lei Cao Nan Tang Ju Fan and Jiayi Wang et al. 2024. MisDetect: Iterative Mislabel Detection using Early Loss. VLDB (2024).

4. Pang Wei Koh and Percy Liang. 2017. Understanding black-box predictions via influence functions. In International conference on machine learning. PMLR.

5. Peng Li, Xi Rao, and Jennifer Blase et al. 2021. CleanML: A Study for Evaluating the Impact of Data Cleaning on ML Classification Tasks. In ICDE 2021. IEEE.

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1. IDE: A System for Iterative Mislabel Detection;Companion of the 2024 International Conference on Management of Data;2024-06-09