Multiview clustering via adaptively weighted procrustes | |
Nie, Feiping1; Tian, Lai1; Li, Xuelong2 | |
2018-07-19 | |
会议名称 | 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2018 |
会议录名称 | KDD 2018 - Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining |
页码 | 2022-2030 |
会议日期 | 2018-08-19 |
会议地点 | London, United kingdom |
出版者 | Association for Computing Machinery |
产权排序 | 2 |
摘要 | In this paper, we make a multiview extension of the spectral rotation technique raised in single view spectral clustering research. Since spectral rotation is closely related to the Procrustes Analysis for points matching, we point out that classical Procrustes Average approach can be used for multiview clustering. Besides, we show that direct applying Procrustes Average (PA) in multiview tasks may not be optimal theoretically and empirically, since it does not take the clustering capacity differences of different views into consideration. Other than that, we propose an Adaptively Weighted Procrustes (AWP) approach to overcome the aforementioned deficiency. Our new AWP weights views with their clustering capacities and forms a weighted Procrustes Average problem accordingly. The optimization algorithm to solve the new model is computational complexity analyzed and convergence guaranteed. Experiments on five real-world datasets demonstrate the effectiveness and efficiency of the new models. © 2018 Association for Computing Machinery. |
作者部门 | 光学影像学习与分析中心 |
DOI | 10.1145/3219819.3220049 |
收录类别 | EI |
ISBN号 | 9781450355520 |
语种 | 英语 |
EI入藏号 | 20183405705515 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/30576 |
专题 | 光谱成像技术研究室 |
作者单位 | 1.School of Computer Science, Center for OPTIMAL, Northwestern Polytechnical University, Xi'an, China; 2.Center for OPTIMAL Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China |
推荐引用方式 GB/T 7714 | Nie, Feiping,Tian, Lai,Li, Xuelong. Multiview clustering via adaptively weighted procrustes[C]:Association for Computing Machinery,2018:2022-2030. |
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 | ||
Multiview clustering(700KB) | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 |
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