Two-Step Greedy Subspace Clustering
文献类型：会议论文
| 作者 | Lingxiao Song1,2 ; Man Zhang1,2; Zhenan Sun1,2; Jian Liang1,2; Ran He(赫然)1,2; Song, Lingxiao
|
| 出版日期 | 2015 |
| 会议日期 | 2015-9 |
| 会议地点 | Gwangju, Korea |
| 关键词 | Greedy Subspace Clustering Sparse Representation Subspace Neighbor |
| 英文摘要 | Greedy subspace clustering methods provide an efficient way to cluster large-scale multimedia datasets. However, these methods do not guarantee a global optimum and their clustering performance mainly depends on their initializations. To alleviate this initialization problem, this paper proposes a two-step greedy strategy by exploring proper neighbors that span an initial subspace. Firstly, for each data point, we seek a sparse representation with respect to its nearest neighbors. The data points corresponding to nonzero entries in the learning representation form an initial subspace, which potentially rejects bad or redundant data points. Secondly, the subspace is updated by adding an orthogonal basis involved with the newly added data points. Experimental results on real-world applications demonstrate that our method can significantly improve the clustering accuracy of greedy subspace clustering methods without scarifying much computational time. |
| 会议录 | Lecture Notes in Computer Science
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/11620]  |
| 专题 | 自动化研究所_智能感知与计算研究中心 |
| 通讯作者 | Song, Lingxiao |
| 作者单位 | 1.Center for Research on Intelligent Perception and Computing 2.Institute of Automation, Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Lingxiao Song,Man Zhang,Zhenan Sun,et al. Two-Step Greedy Subspace Clustering[C]. 见:. Gwangju, Korea. 2015-9. |
入库方式： OAI收割
来源：自动化研究所
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