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检索条件"主题词=Nonnegative Matrix factorization"
1480 条 记 录,以下是231-240 订阅
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Learning of nonnegative matrix factorization Models for Inconsistent Resolution Dataset Analysis
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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2019年 第4期E102D卷 715-723页
作者: Kohjima, Masahiro Matsubayashi, Tatsushi Sawada, Hiroshi NTT Serv Evolut Labs Yokosuka Kanagawa 2390847 Japan
Due to the need to protect personal information and the impracticality of exhaustive data collection, there is increasing need to deal with datasets with various levels of granularity, such as user-individual data and... 详细信息
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A deep discriminative and robust nonnegative matrix factorization network method with soft label constraint
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NEURAL COMPUTING & APPLICATIONS 2019年 第11期31卷 7447-7475页
作者: Tong, Ming Chen, Yiran Zhao, Mengao Bu, Haili Xi, Shengnan Xidian Univ Sch Elect Engn Xian 710071 Peoples R China
In order to obtain a discriminative, compact and robust data representation, a discriminative and robust nonnegative matrix factorization method with soft label constraint (DRNMF_SLC) is proposed. By minimizing the ob... 详细信息
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Simultaneous Dimensionality Reduction and Classification via Dual Embedding Regularized nonnegative matrix factorization
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IEEE TRANSACTIONS ON IMAGE PROCESSING 2019年 第8期28卷 3836-3847页
作者: Wu, Wenhui Kwong, Sam Hou, Junhui Jia, Yuheng Ip, Horace Ho Shing City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China City Univ Hong Kong Shenzhen Res Inst Shenzhen 51800 Peoples R China
nonnegative matrix factorization (NMF) is a well-known paradigm for data representation. Traditional NMF-based classification methods first perform NMF or one of its variants on input data samples to obtain their low-... 详细信息
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A discriminant graph nonnegative matrix factorization approach to computer vision
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NEURAL COMPUTING & APPLICATIONS 2019年 第11期31卷 7879-7889页
作者: Dai, Xiangguang Chen, Guo Li, Chuandong Southwest Univ Natl & Local Joint Engn Lab Intelligent Transmiss Coll Elect & Informat Engn Chongqing 400715 Peoples R China Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia
This paper proposes a novel dimensional reduction method, called discriminant graph nonnegative matrix factorization (DGNMF), for image representation. Inspired by manifold learning and linear discrimination analysis,... 详细信息
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Hyperplane-based nonnegative matrix factorization with label information
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INFORMATION SCIENCES 2019年 493卷 1-19页
作者: Peng, Xinjun Chen, De Xu, Dong Shanghai Normal Univ Dept Math Shanghai 200234 Peoples R China
As one commonly used dimensionality reduction method, nonnegative matrix factorization (NMF), whose goal is to learn parts-based representations, has been widely studied and applied to various areas. However, classica... 详细信息
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Self-paced and soft-weighted nonnegative matrix factorization for data representation
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KNOWLEDGE-BASED SYSTEMS 2019年 164卷 29-37页
作者: Huang, Shudong Zhao, Peng Ren, Yazhou Li, Tianrui Xu, Zenglin Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu 611731 Sichuan Peoples R China Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu 611756 Sichuan Peoples R China
nonnegative matrix factorization (NMF) has received intensive attention due to producing a parts-based representation of the data. However, because of the non-convexity of NMF models, these methods easily obtain a bad... 详细信息
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Novel Algorithms Based on Majorization Minimization for nonnegative matrix factorization
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IEEE ACCESS 2019年 7卷 115682-115695页
作者: Jyothi, R. Babu, Prabhu Bahl, Rajendar IIT Delhi CARE New Delhi 110016 India
matrix decomposition is ubiquitous and has applications in various fields like speech processing, data mining and image processing to name a few. Under matrix decomposition, nonnegative matrix factorization is used to... 详细信息
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Network Embedding Using Semi-Supervised Kernel nonnegative matrix factorization
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IEEE ACCESS 2019年 7卷 92732-92744页
作者: He, Chaobo Zhang, Qiong Tang, Yong Liu, Shuangyin Liu, Hai Zhongkai Univ Agr & Engn Sch Informat Sci & Technol Guangzhou 510225 Guangdong Peoples R China Hubei Univ Sch Comp Sci & Informat Engn Wuhan 430062 Hubei Peoples R China South China Normal Univ Sch Comp Sci Guangzhou 510631 Guangdong Peoples R China Hyperhunch Technol Ltd Shenzhen 518000 Peoples R China
Network embedding, aiming to learn low-dimensional representations of nodes in networks, is very useful for many vector-based machine learning algorithms and has become a hot research topic in network analysis. Althou... 详细信息
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Enhancing Hyperspectral Unmixing With Two-Stage Multiplicative Update nonnegative matrix factorization
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IEEE ACCESS 2019年 7卷 171023-171031页
作者: Sun, Li Zhao, Kang Han, Congying Liu, Ziwen Shandong Agr Univ Coll Informat Sci & Engn Tai An 271000 Shandong Peoples R China Univ Iowa Dept Management Sci Iowa City IA 52242 USA Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China
nonnegative matrix factorization (NMF) is a powerful tool for hyperspectral unmixing (HU). This method factorizes a hyperspectral cube into constituent endmembers and their fractional abundances. In this paper, we pro... 详细信息
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A neurodynamics-based nonnegative matrix factorization approach based on discrete-time projection neural network
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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2019年 第12期14卷 1-9页
作者: Zhang, Nian Leatham, Keenan Univ Dist Columbia Dept Elect & Comp Engn Washington DC 20008 USA
This paper contributes to study the influence of various NMF algorithms on the classification accuracy of each classifier as well as to compare the classifiers among themselves. We focus on a fast nonnegative matrix f... 详细信息
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