Multi-view clustering and semi-supervised classification with adaptive neighbours | |
Nie, Feiping1; Cai, Guohao1; Li, Xuelong2 | |
2017 | |
会议名称 | 31st AAAI Conference on Artificial Intelligence, AAAI 2017 |
会议录名称 | 31st AAAI Conference on Artificial Intelligence, AAAI 2017 |
页码 | 2408-2414 |
会议日期 | 2017-02-04 |
会议地点 | San Francisco, CA, United states |
出版者 | AAAI press |
产权排序 | 2 |
摘要 | Due to the efficiency of learning relationships and complex structures hidden in data, graph-oriented methods have been widely investigated and achieve promising performance in multi-view learning. Generally, these learning algorithms construct informative graph for each view or fuse different views to one graph, on which the following procedure are based. However, in many real world dataset, original data always contain noise and outlying entries that result in unreliable and inaccurate graphs, which cannot be ameliorated in the previous methods. In this paper, we propose a novel multi-view learning model which performs clustering/semi-supervised classification and local structure learning simultaneously. The obtained optimal graph can be partitioned into specific clusters directly. Moreover, our model can allocate ideal weight for each view automatically without additional weight and penalty parameters. An efficient algorithm is proposed to optimize this model. Extensive experimental results on different real-world datasets show that the proposed model outperforms other state-of-the-art multi-view algorithms. © Copyright 2017, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. |
作者部门 | 光学影像学习与分析中心 |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/29403 |
专题 | 光谱成像技术研究室 |
作者单位 | 1.School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi'an, Shaanxi; 710072, China 2.Center for OPTical IMagery Analysis and Learning (OPTIMAL), Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi; 710119, China |
推荐引用方式 GB/T 7714 | Nie, Feiping,Cai, Guohao,Li, Xuelong. Multi-view clustering and semi-supervised classification with adaptive neighbours[C]:AAAI press,2017:2408-2414. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Multi-view clusterin(682KB) | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 |
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