中国科学院沈阳自动化研究所机构知识库
Advanced  
SIA OpenIR  > 机器人学研究室  > 会议论文
题名:
Robust tensor factorization with unknown noise
作者: Chen XA(陈希爱); Han Z(韩志); Wang, Yao; Zhao, Qian; Meng, Deyu; Tang YD(唐延东)
作者部门: 机器人学研究室
通讯作者: 韩志
会议名称: 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
会议日期: June 26 - July 1, 2016
会议地点: Las Vegas, NV, United states
会议主办者: 2016-January
会议录: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
会议录出版者: IEEE Computer Society
会议录出版地: Washington, DC
出版日期: 2016
页码: 5213-5221
收录类别: EI
ISSN号: 1063-6919
ISBN号: 978-1-4673-8851-1
摘要: Because of the limitations of matrix factorization, such as losing spatial structure information, the concept of tensor factorization has been applied for the recovery of a low dimensional subspace from high dimensional visual data. Generally, the recovery is achieved by minimizing the loss function between the observed data and the factorization representation. Under different assumptions of the noise distribution, the loss functions are in various forms, like L1and L2norms. However, real data are often corrupted by noise with an unknown distribution. Then any specific form of loss function for one specific kind of noise often fails to tackle such real data with unknown noise. In this paper, we propose a tensor factorization algorithm to model the noise as a Mixture of Gaussians (MoG). As MoG has the ability of universally approximating any hybrids of continuous distributions, our algorithm can effectively recover the low dimensional subspace from various forms of noisy observations. The parameters of MoG are estimated under the EM framework and through a new developed algorithm of weighted low-rank tensor factorization (WLRTF). The effectiveness of our algorithm are substantiated by extensive experiments on both of synthetic data and real image data.
语种: 英语
产权排序: 1
EI收录号: 20163702804679
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/19197
Appears in Collections:机器人学研究室_会议论文

Files in This Item: Download All
File Name/ File Size Content Type Version Access License
Robust tensor factorization with unknown noise.pdf(3132KB)会议论文--开放获取View Download

Recommended Citation:
Chen XA,Han Z,Wang, Yao,et al. Robust tensor factorization with unknown noise[C]. 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016. Las Vegas, NV, United states. June 26 - July 1, 2016.Robust tensor factorization with unknown noise.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Chen XA(陈希爱)]'s Articles
[Han Z(韩志)]'s Articles
[Wang, Yao]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Chen XA(陈希爱)]‘s Articles
[Han Z(韩志)]‘s Articles
[Wang, Yao]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: Robust tensor factorization with unknown noise.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2017  中国科学院沈阳自动化研究所 - Feedback
Powered by CSpace