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Unimodal regularized neuron stick-breaking for ordinal classification
X. F. Liu; F. F. Fan; L. S. Kong; Z. H. Diao; W. Q. Xie; J. Lu and J. N. You
2020
发表期刊Neurocomputing
ISSN0925-2312
卷号388页码:34-44
摘要This paper targets for the ordinal regression/classification, which objective is to learn a rule to predict labels from a discrete but ordered set. For instance, the classification for medical diagnosis usually involves inherently ordered labels corresponding to the level of health risk. Previous multi-task classifiers on ordinal data often use several binary classification branches to compute a series of cumulative probabilities. However, these cumulative probabilities are not guaranteed to be monotonically decreasing. It also introduces a large number of hyper-parameters to be fine-tuned manually. This paper aims to eliminate or at least largely reduce the effects of those problems. We propose a simple yet efficient way to rephrase the output layer of the conventional deep neural network. Besides, in order to alleviate the effects of label noise in ordinal datasets, we propose a unimodal label regularization strategy. It also explicitly encourages the class predictions to distribute on nearby classes of ground truth. We show that our methods lead to the state-of-the-art accuracy on the medical diagnose task (e.g., Diabetic Retinopathy and Ultrasound Breast dataset) as well as the face age prediction (e.g., Adience face and MORPH Album II) with very little additional cost. (C) 2020 Elsevier B.V. All rights reserved.
DOI10.1016/j.neucom.2020.01.025
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收录类别SCI
语种英语
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文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/64994
专题中国科学院长春光学精密机械与物理研究所
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GB/T 7714
X. F. Liu,F. F. Fan,L. S. Kong,et al. Unimodal regularized neuron stick-breaking for ordinal classification[J]. Neurocomputing,2020,388:34-44.
APA X. F. Liu,F. F. Fan,L. S. Kong,Z. H. Diao,W. Q. Xie,&J. Lu and J. N. You.(2020).Unimodal regularized neuron stick-breaking for ordinal classification.Neurocomputing,388,34-44.
MLA X. F. Liu,et al."Unimodal regularized neuron stick-breaking for ordinal classification".Neurocomputing 388(2020):34-44.
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