Ensemble Active Learning by Contextual Bandits for AI Incubation in Manufacturing
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Abstract (arXiv)
It is challenging but important to save annotation efforts in streaming data acquisition to maintain data quality for supervised learning base learners. We propose an ensemble active learning method to actively acquire samples for annotation by contextual bandits, which is will enforce the exploration-exploitation balance and leading to improved AI modeling performance.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 4 of its 84 references that are in the map. First posted on arXiv 10 Oct 2023.
Builds on
4 of 84 references.
References · 4
- 2013Bandits with Knapsackscited by 163
- 2021Poisoning the Unlabeled Dataset of Semi-Supervised Learningcited by 44
- 2019Better Data Labelling with EMBLEM (and how that Impacts Defect Prediction)cited by 13
- 2019AKM2D : An Adaptive Framework for Online Sensing and Anomaly Quantificationcited by 3
Built on by
Citing papers per year: 2024: 2; 2025: 3.
5 papers.
- 2025Survey: Multi-Armed Bandits Meet Large Language Modelscited by 6
- 2025Efficient Implementation of LinearUCB through Algorithmic Improvements and Vector Computing Acceleration for Embedded Learning Systemscited by 4
- 2025FAIR: Facilitating Artificial Intelligence Resilience in Manufacturing Industrial Internetcited by 1
- 2024Root Cause Analysis Of Productivity Losses In Manufacturing Systems Utilizing Ensemble Machine Learningcited by 0
- 2024Stream-Based Active Learning for Process Monitoringcited by 0
- 2025Survey: Multi-Armed Bandits Meet Large Language Models19 May 2025
- 2025FAIR: Facilitating Artificial Intelligence Resilience in Manufacturing Industrial Internet3 Mar 2025
- 2025Efficient Implementation of LinearUCB through Algorithmic Improvements and Vector Computing Acceleration for Embedded Learning Systems22 Jan 2025
- 2024Stream-Based Active Learning for Process Monitoring19 Nov 2024
- 2024Root Cause Analysis Of Productivity Losses In Manufacturing Systems Utilizing Ensemble Machine Learning31 Jul 2024