| Self-representative manifold concept factorization with adaptive neighbors for clustering | |
| Ma, Sihan1; Zhang, Lefei1; Hu, Wenbin1; Zhang, Yipeng1; Wu, Jia2; Li, Xuelong3 | |
| 2018 | |
| 会议名称 | 27th International Joint Conference on Artificial Intelligence, IJCAI 2018 |
| 会议录名称 | Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018 |
| 卷号 | 2018-July |
| 页码 | 2539-2545 |
| 会议日期 | 2018-07-13 |
| 会议地点 | Stockholm, Sweden |
| 出版者 | International Joint Conferences on Artificial Intelligence |
| 产权排序 | 3 |
| 摘要 | Matrix Factorization based methods, e.g., the Concept Factorization (CF) and Nonnegative Matrix Factorization (NMF), have been proved to be efficient and effective for data clustering tasks. In recent years, various graph extensions of CF and NMF have been proposed to explore intrinsic geometrical structure of data for the purpose of better clustering performance. However, many methods build the affinity matrix used in the manifold structure directly based on the input data. Therefore, the clustering results are highly sensitive to the input data. To further improve the clustering performance, we propose a novel manifold concept factorization model with adaptive neighbor structure to learn a better affinity matrix and clustering indicator matrix at the same time. Technically, the proposed model constructs the affinity matrix by assigning the adaptive and optimal neighbors to each point based on the local distance of the learned new representation of the original data with itself as a dictionary. Our experimental results present superior performance over the state-of-the-art alternatives on numerous datasets. © 2018 International Joint Conferences on Artificial Intelligence. All right reserved. |
| 作者部门 | 光学影像学习与分析中心 |
| 收录类别 | EI |
| ISBN号 | 9780999241127 |
| 语种 | 英语 |
| ISSN号 | 10450823 |
| EI入藏号 | 20184406016257 |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/30698 |
| 专题 | 光谱成像技术研究室 |
| 通讯作者 | Zhang, Lefei |
| 作者单位 | 1.School of Computer, Wuhan University, United Kingdom; 2.Department of Computing, Macquarie University, United Kingdom; 3.Center for OPTIMAL, Xi'an Institute of Optics and Precision Mechanics, CAS, United Kingdom |
| 推荐引用方式 GB/T 7714 | Ma, Sihan,Zhang, Lefei,Hu, Wenbin,et al. Self-representative manifold concept factorization with adaptive neighbors for clustering[C]:International Joint Conferences on Artificial Intelligence,2018:2539-2545. |
| 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 | ||
| Self-representative （129KB） | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 | ||
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