中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 多模态人工智能系统全国重点实验室
  5. 模式分析与学习团队
SubMIL: Discriminative subspaces for multi-instance learning

文献类型：期刊论文

作者Yuan, Jiazheng1,2; Huang, Xiankai3; Liu, Hongzhe1; Li, Bing4; Xiong, Weihua4
刊名NEUROCOMPUTING
出版日期2016-01-15
卷号173页码:1768-1774
关键词Multi-instance learning Low rank Subspace
英文摘要As an important learning scheme for Multi-Instance Learning (MIL), the Instance Prototype (IP) selection-based MIL algorithms transform bags into a new instance feature space and achieve impressed classification performance. However, the number of IPs in the existing algorithms linearly increases with the scale of the training data. The performance and efficiencies of these algorithms are easily limited by the high dimension and noise when facing a large scale of training data. This paper proposes a discriminative subspaces-based instance prototype selection method that is suitable for reducing the computation complexity for large scale training data. In the proposed algorithm, we introduce the low-rank matrix recovery technique to find two discriminative and clean subspaces with less noise; then present a l(2,1) norm-based self-expressive sparse coding model to select the most representative instances in each subspace. Experimental results on several data sets show that our algorithm achieves superior and stable performance but with lower dimension compared with other IP selection strategies. (C) 2015 Elsevier B.V. All rights reserved.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence
研究领域[WOS]Computer Science
关键词[WOS]ALGORITHM ; SELECTION
收录类别SCI
语种英语
WOS记录号WOS:000366879800129
源URL[http://ir.ia.ac.cn/handle/173211/10645]  
专题自动化研究所_模式识别国家重点实验室_模式分析与学习团队
作者单位1.Beijing Key Lab Informat Serv Engn, Beijing 100101, Peoples R China
2.Beijing Union Univ, Comp Technol Inst, Beijing 100101, Peoples R China
3.Beijing Union Univ, Tourism Inst, Beijing 100101, Peoples R China
4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit NLPR, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Yuan, Jiazheng,Huang, Xiankai,Liu, Hongzhe,et al. SubMIL: Discriminative subspaces for multi-instance learning[J]. NEUROCOMPUTING,2016,173:1768-1774.
APA Yuan, Jiazheng,Huang, Xiankai,Liu, Hongzhe,Li, Bing,&Xiong, Weihua.(2016).SubMIL: Discriminative subspaces for multi-instance learning.NEUROCOMPUTING,173,1768-1774.
MLA Yuan, Jiazheng,et al."SubMIL: Discriminative subspaces for multi-instance learning".NEUROCOMPUTING 173(2016):1768-1774.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。