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Less annotation on active learning using confidence-weighted predictions

文献类型：期刊论文

作者Yang, Xiaodong1,2,3,4; Chen, Yiqiang1,2,3,4; Yu, Hanchao1,2,4; Zhang, Yingwei1,2,3,4
刊名NEUROCOMPUTING
出版日期2018-01-31
卷号275页码:1629-1636
关键词Extreme Learning Machine Online sequential learning Active learning Less annotation
ISSN号0925-2312
DOI10.1016/j.neucom.2017.10.004
英文摘要This paper proposes an efficient and effective active online sequential learning approach, named as Less Annotated Active Learning Extreme Learning Machine (LAAL-ELM). It leverages the predictions' confidence of the new arriving data to actively select both query-annotated samples and confidence-weighted predict-annotated ones to update the classifier, which contributes to less actively query annotation, and applies WOS-ELM, a discriminant model, to significantly reduce the computation complexity for doing online updating in one step. The proposed approach firstly gives a principle to evaluate confidence of the prediction in WOS-ELM; then determines what and how to update the model with new arriving data in the online phase: the uncertain instances are annotated by query their classes, almost-certain ones are weighted on its prediction's confidence and the certain ones are discarded directly for reducing over-fitting; at last, the weighted and query-annotated samples are used to update the classifier. The proposed approach is evaluated on five real-world benchmark classification issues. And the experimental results demonstrate that the proposed LAAL-ELM can effectively reduce the number of queried samples while maintaining high level of classification performance. (c) 2017 Elsevier B.V. All rights reserved.
资助项目Natural Science Foundation of China[61502456] ; Natural Science Foundation of China[61572471] ; Science and Technology Planning Project of Guangdong Province, China[2015B010105001] ; Beijing Municipal Science & Technology Commission[Z161100000216140] ; Beijing Municipal Science & Technology Commission[Z171100000117013]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000418370200153
出版者ELSEVIER SCIENCE BV
源URL[http://119.78.100.204/handle/2XEOYT63/6278]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Chen, Yiqiang
作者单位1.Beijing Key Lab Parkinsons Dis, Beijing 100053, Peoples R China
2.Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Xiaodong,Chen, Yiqiang,Yu, Hanchao,et al. Less annotation on active learning using confidence-weighted predictions[J]. NEUROCOMPUTING,2018,275:1629-1636.
APA Yang, Xiaodong,Chen, Yiqiang,Yu, Hanchao,&Zhang, Yingwei.(2018).Less annotation on active learning using confidence-weighted predictions.NEUROCOMPUTING,275,1629-1636.
MLA Yang, Xiaodong,et al."Less annotation on active learning using confidence-weighted predictions".NEUROCOMPUTING 275(2018):1629-1636.

入库方式： OAI收割

来源：计算技术研究所

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