[1]YIN Jianhua,LIU Zhenbing,WEI Huangzhao.Partial label classification algorithm based on sparse reconstruction disambiguation[J].CAAI Transactions on Intelligent Systems,2023,18(4):708-718.[doi:10.11992/tis.202202024]
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Partial label classification algorithm based on sparse reconstruction disambiguation
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
18
Number of periods:
2023 4
Page number:
708-718
Column:
学术论文—机器学习
Public date:
2023-07-15
- Title:
- Partial label classification algorithm based on sparse reconstruction disambiguation
- Keywords:
- weakly supervised learning; sparse reconstruction; smoothness assumption; label disambiguation; partial label learning; candidate label; feature space; multi-classification
- CLC:
- TP181
- DOI:
- 10.11992/tis.202202024
- Abstract:
- Most of the existing partial label learning (PLL) methods neither ignores making full use of potentially useful information from feature space, nor considers different labeling confidence levels of the candidate labels in the disambiguation process. In this paper, we propose a novel approach for partial label learning by sparse reconstruction disambiguation (PL-SRD), which facilitates the labeling disambiguation process by leveraging the structural information in feature space. We first characterize the topological structure of feature space by conducting sparse reconstruction among the training examples and integrate it into the label disambiguation process. Then, we present a unified framework, which performs label disambiguation and predictive model training simultaneously. Extensive experimental results on both artificial and real-world datasets demonstrate the superiority of our method to other state-of-the-art PLL methods.
- References:
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1900-01-01