Supervised tensor learning
文献类型：期刊论文
| 作者 | Dacheng Tao; Xuelong Li; Xindong Wu; Weiming Hu ; Stephen J. Maybank
|
| 刊名 | KNOWLEDGE AND INFORMATION SYSTEMS
 |
| 出版日期 | 2007-09-01 |
| 卷号 | 13期号:1页码:1-42 |
| 关键词 | convex optimization supervised learning tensor alternating projection |
| 英文摘要 | Tensor representation is helpful to reduce the small sample size problem in discriminative subspace selection. As pointed by this paper, this is mainly because the structure information of objects in computer vision research is a reasonable constraint to reduce the number of unknown parameters used to represent a learning model. Therefore, we apply this information to the vector-based learning and generalize the vector-based learning to the tensor-based learning as the supervised tensor learning (STL) framework, which accepts tensors as input. To obtain the solution of STL, the alternating projection optimization procedure is developed. The STL framework is a combination of the convex optimization and the operations in multilinear algebra. The tensor representation helps reduce the overfitting problem in vector-based learning. Based on STL and its alternating projection optimization procedure, we generalize support vector machines, minimax probability machine, Fisher discriminant analysis, and distance metric learning, to support tensor machines, tensor minimax probability machine, tensor Fisher discriminant analysis, and the multiple distance metrics learning, respectively. We also study the iterative procedure for feature extraction within STL. To examine the effectiveness of STL, we implement the tensor minimax probability machine for image classification. By comparing with minimax probability machine, the tensor version reduces the overfitting problem. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Information Systems |
| 研究领域[WOS] | Computer Science |
| 关键词[WOS] | VISUAL-ATTENTION ; SUPPORT VECTOR ; DISCRIMINANT-ANALYSIS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000249657900001 |
| 公开日期 | 2015-12-24 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/9439]  |
| 专题 | 自动化研究所_09年以前成果 |
| 作者单位 | 1.Univ London, Sch Comp Sci & Informat Syst, London, England 2.Univ Vermont, Dept Comp Sci, Burlington, VT USA 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Regnit, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Dacheng Tao,Xuelong Li,Xindong Wu,et al. Supervised tensor learning[J]. KNOWLEDGE AND INFORMATION SYSTEMS,2007,13(1):1-42. |
| APA | Dacheng Tao,Xuelong Li,Xindong Wu,Weiming Hu,&Stephen J. Maybank.(2007).Supervised tensor learning.KNOWLEDGE AND INFORMATION SYSTEMS,13(1),1-42. |
| MLA | Dacheng Tao,et al."Supervised tensor learning".KNOWLEDGE AND INFORMATION SYSTEMS 13.1(2007):1-42. |
入库方式： OAI收割
来源：自动化研究所
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