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张宪超
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教授   博士生导师   硕士生导师

主要任职: 国防(先进)科学技术发展研究院副院长

性别: 男

毕业院校: 中国科技大学

学位: 博士

在职信息:在职

所在单位: 软件学院

学科: 计算机应用技术 软件工程

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SPGLAD: A Self-paced Learning-Based Crowdsourcing Classification Model

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论文类型: 会议论文

第一作者: Zhang, Xianchao

合写作者: Shi, Heng,Li, Yuangang,Liang, Wenxin

发表时间: 2017-01-01

发表刊物: TRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MINING, 2017

收录刊物: EI、CPCI-S

卷号: 10526

页面范围: 189-201

关键字: Crowdsourcing; Self-paced learning; Quality control

摘要: Crowdsourcing platforms like Amazon's Mechanical Turk provide fast and effective solutions of collecting massive datasets for performing tasks in domains such as image classification, information retrieval, etc. Crowdsourcing quality control plays an essential role in such systems. However, existing algorithms are prone to get stuck in a bad local optimum because of ill-defined datasets. To overcome the above drawbacks, we propose a novel self-paced quality control model integrating a priority-based sample-picking strategy. The proposed model ensures the evident samples do better efforts during iterations. We also empirically demonstrate that the proposed self-paced learning strategy promotes common quality control methods.

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