Scalable Linear Visual Feature Learning via Online Parallel Nonnegative Matrix Factorization | |
Zhao, Xueyi1; Li, Xi2; Zhang, Zhongfei1,3; Shen, Chunhua4; Zhuang, Yueting2; Gao, Lixin5; Li, Xuelong6; Li, X (reprint author), Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China. | |
作者部门 | 光学影像学习与分析中心 |
2016-12-01 | |
发表期刊 | IEEE Transactions on Neural Networks and Learning Systems |
ISSN | 2162-237X |
卷号 | 27期号:12页码:2628-2642 |
产权排序 | 6 |
摘要 | Visual feature learning, which aims to construct an effective feature representation for visual data, has a wide range of applications in computer vision. It is often posed as a problem of nonnegative matrix factorization (NMF), which constructs a linear representation for the data. Although NMF is typically parallelized for efficiency, traditional parallelization methods suffer from either an expensive computation or a high runtime memory usage. To alleviate this problem, we propose a parallel NMF method called alternating least square block decomposition (ALSD), which efficiently solves a set of conditionally independent optimization subproblems based on a highly parallelized fine-grained grid-based blockwise matrix decomposition. By assigning each block optimization subproblem to an individual computing node, ALSD can be effectively implemented in a MapReduce-based Hadoop framework. In order to cope with dynamically varying visual data, we further present an incremental version of ALSD, which is able to incrementally update the NMF solution with a low computational cost. Experimental results demonstrate the efficiency and scalability of the proposed methods as well as their applications to image clustering and image retrieval. |
文章类型 | Article |
关键词 | Feature Learning Nonnegative Matrix Factorization (Nmf) Online Algorithm Parallel Computing |
学科领域 | Computer Science, Artificial Intelligence |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1109/TNNLS.2015.2499273 |
收录类别 | SCI ; EI |
关键词[WOS] | IMAGE REPRESENTATION ; NMF ; MODELS |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering |
项目资助者 | National Natural Science Foundation of China(61472353) ; China Knowledge Centre for Engineering Sciences and Technology within the Key Research Program through the Chinese Academy of Sciences(KGZD-EW-T03) ; National Basic Research Program of China(2012CB316400 ; Fundamental Research Funds for the Central Universities ; Zhejiang Provincial Engineering Center on Media Data Cloud Processing and Analysis ; Microsoft Research Asia Collaborative Research Program ; MOE-Microsoft Key Laboratory, Zhejiang University ; U.S. National Science Foundation (NSF)(CCF-1017828) ; U.S. NSF(CNS-1217284 ; 2015CB352300) ; CCF-1018114) |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000388919600014 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/28562 |
专题 | 光谱成像技术研究室 |
通讯作者 | Li, X (reprint author), Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China. |
作者单位 | 1.Zhejiang Univ, Dept Informat Sci & Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China 2.Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China 3.SUNY Binghamton, Watson Sch, Dept Comp Sci, Binghamton, NY 13902 USA 4.Univ Adelaide, Sch Comp Sci, Adelaide, SA 5005, Australia 5.Univ Massachusetts, Amherst, MA 01003 USA 6.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Zhao, Xueyi,Li, Xi,Zhang, Zhongfei,et al. Scalable Linear Visual Feature Learning via Online Parallel Nonnegative Matrix Factorization[J]. IEEE Transactions on Neural Networks and Learning Systems,2016,27(12):2628-2642. |
APA | Zhao, Xueyi.,Li, Xi.,Zhang, Zhongfei.,Shen, Chunhua.,Zhuang, Yueting.,...&Li, X .(2016).Scalable Linear Visual Feature Learning via Online Parallel Nonnegative Matrix Factorization.IEEE Transactions on Neural Networks and Learning Systems,27(12),2628-2642. |
MLA | Zhao, Xueyi,et al."Scalable Linear Visual Feature Learning via Online Parallel Nonnegative Matrix Factorization".IEEE Transactions on Neural Networks and Learning Systems 27.12(2016):2628-2642. |
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Scalable Linear Visu(3419KB) | 期刊论文 | 作者接受稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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