A Comparative Survey : Benchmarking for Pool-based Active Learning
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21) |
Editors | Zhi-Hua Zhou |
Publisher | International Joint Conferences on Artificial Intelligence |
Pages | 4679-4686 |
ISBN (electronic) | 978-0-9992411-9-6 |
Publication status | Published - Aug 2021 |
Publication series
Name | IJCAI International Joint Conference on Artificial Intelligence |
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ISSN (Print) | 1045-0823 |
Conference
Title | 30th International Joint Conference on Artificial Intelligence (IJCAI 2021) |
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Location | Virtual, Online |
Place | Canada |
Period | 19 - 27 August 2021 |
Link(s)
Abstract
Active learning (AL) is a subfield of machine learning (ML) in which a learning algorithm aims to achieve good accuracy with fewer training samples by interactively querying the oracles to label new data points. Pool-based AL is well-motivated in many ML tasks, where unlabeled data is abundant, but their labels are hard or costly to obtain. Although many pool-based AL methods have been developed, some important questions remain unanswered such as how to: 1) determine the current state-of-the-art technique; 2) evaluate the relative benefit of new methods for various properties of the dataset; 3) understand what specific problems merit greater attention; and 4) measure the progress of the field over time. In this paper, we survey and compare various AL strategies used in both recently proposed and classic highly-cited methods. We propose to benchmark pool-based AL methods with a variety of datasets and quantitative metric, and draw insights from the comparative empirical results.
Citation Format(s)
A Comparative Survey: Benchmarking for Pool-based Active Learning. / Zhan, Xueying; Liu, Huan; Li, Qing et al.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21) . ed. / Zhi-Hua Zhou. International Joint Conferences on Artificial Intelligence, 2021. p. 4679-4686 (IJCAI International Joint Conference on Artificial Intelligence).
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21) . ed. / Zhi-Hua Zhou. International Joint Conferences on Artificial Intelligence, 2021. p. 4679-4686 (IJCAI International Joint Conference on Artificial Intelligence).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review