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Adaptive-weighted deep multi-view clustering with uniform scale representation
期刊论文
NEURAL NETWORKS, 2024, 卷号: 171, 页码: 114-126
作者:
Chen, Rui
;
Tang, Yongqiang
;
Zhang, Wensheng
;
Feng, Wenlong
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2024/02/21
Multi-view clustering
Deep clustering
Adaptive-weighted learning
Uniform scale representation
Affine Subspace Robust Low-Rank Self-Representation: From Matrix to Tensor
期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 8, 页码: 9357-9373
作者:
Tang, Yongqiang
;
Xie, Yuan
;
Zhang, Wensheng
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  |  
浏览/下载:2/0
  |  
提交时间:2023/11/17
Affine subspace
low-rank representation
low-rank tensor
multi-view learning
subspace clustering
fi-divergence NMF with biorthogonal regularization for data representation
期刊论文
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2023, 卷号: 121, 页码: 14
作者:
Yuan, Ruixue
;
Leng, Chengcai
;
Li, Bing
;
Basu, Anup
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  |  
浏览/下载:2/0
  |  
提交时间:2023/11/17
NMF
fi-divergence
Biorthogonal regularization
Clustering
Proximal Alternating-Direction-Method-of- Multipliers-Incorporated Nonnegative Latent Factor Analysis
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 6, 页码: 1388-1406
作者:
Fanghui Bi
;
Xin Luo
;
Bo Shen
;
Hongli Dong
;
Zidong Wang
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  |  
浏览/下载:7/0
  |  
提交时间:2023/05/29
Data science
high-dimensional and incomplete data
knowledge acquisition
industrial application
nonnegative latent factor analysis (NLFA)
proximal alternating direction method of multipliers
representation learning
Robust Kernelized Multiview Self-Representation for Subspace Clustering
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 2, 页码: 868-881
作者:
Xie, Yuan
;
Liu, Jinyan
;
Qu, Yanyun
;
Tao, Dacheng
;
Zhang, Wensheng
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  |  
浏览/下载:49/0
  |  
提交时间:2021/03/29
Tensile stress
Kernel
Manifolds
Optimization
Learning systems
Correlation
Data models
Kernelization
multiview subspace learning
nonlinear subspace clustering
tensor singular value decomposition (t-SVD)
Improved Symmetric and Nonnegative Matrix Factorization Models for Undirected, Sparse and Large-Scaled Networks: A Triple Factorization-Based Approach
期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 卷号: 16, 期号: 5, 页码: 3006-3017
作者:
Song, Yan
;
Li, Ming
;
Luo, Xin
;
Yang, Guisong
;
Wang, Chongjing
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  |  
浏览/下载:40/0
  |  
提交时间:2020/08/24
Computational modeling
Sparse matrices
Biological system modeling
Symmetric matrices
Matrix decomposition
Linear programming
Convergence
Big data
data analysis
latent factor
nonnegativity
sparse and large-scaled network
symmetry
triple-factorization
undirected
Deep Learning Based Speech Separation via NMF-Style Reconstructions
期刊论文
IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2018, 卷号: 26, 期号: 11, 页码: 2043-2055
作者:
Nie, Shuai
;
Liang, Shan
;
Liu, Wenju
;
Zhang, Xueliang
;
Tao, Jianhua
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  |  
浏览/下载:22/0
  |  
提交时间:2018/10/10
Speech Separation
Deep Neural Network (Dnn)
Nonnegative Matrix Factorization (Nmf)
Spectro-temporal Structures
Discriminative and orthogonal subspace constraints-based nonnegative matrix factorization
期刊论文
ACM Transactions on Intelligent Systems and Technology, 2018, 卷号: 9, 期号: 6
作者:
Li, Xuelong
;
Cui, Guosheng
;
Dong, Yongsheng
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  |  
浏览/下载:62/0
  |  
提交时间:2019/03/04
Deep Learning Based Speech Separation via NMF-style Reconstructions
期刊论文
IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, 2018, 卷号: 26, 期号: 11, 页码: 2043-2055
作者:
Shuai Nie
;
Shan Liang
;
Wenju Liu
;
Xueliang Zhang
;
Jianhua Tao
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2020/10/22
Speech separation
deep neural network (DNN)
nonnegative matrix factorization (NMF)
spectro-temporal structures
An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications
期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2018, 卷号: 14, 期号: 5, 页码: 2011-2022
作者:
Luo, Xin
;
Zhou, MengChu
;
Li, Shuai
;
Shang, MingSheng
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  |  
浏览/下载:33/0
  |  
提交时间:2018/07/02
Big data
high-dimensional and sparse matrix
learning algorithms
missing-data estimation
nonnegative latent factor analysis
optimization methods recommender system
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