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Title
Learnable low-rank latent dictionary for subspace clustering
Authors
Keywords
Subspace clustering, Low-rank, Feature extraction, Block diagonal representation
Journal
PATTERN RECOGNITION
Volume 120, Issue -, Pages 108142
Publisher
Elsevier BV
Online
2021-06-29
DOI
10.1016/j.patcog.2021.108142
References
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Related references
Note: Only part of the references are listed.- Autoencoder-Based Latent Block-Diagonal Representation for Subspace Clustering
- (2020) Yesong Xu et al. IEEE Transactions on Cybernetics
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- (2017) Lunke Fei et al. PATTERN RECOGNITION
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- (2017) Jun Li et al. IEEE Transactions on Neural Networks and Learning Systems
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- (2016) Ming Yin et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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- (2016) Qi Li et al. PATTERN RECOGNITION
- Robust Kernel Low-Rank Representation
- (2016) Shijie Xiao et al. IEEE Transactions on Neural Networks and Learning Systems
- ImageNet Large Scale Visual Recognition Challenge
- (2015) Olga Russakovsky et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Sparse Subspace Clustering: Algorithm, Theory, and Applications
- (2013) E. Elhamifar et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Robust Recovery of Subspace Structures by Low-Rank Representation
- (2012) Guangcan Liu et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Subspace Clustering
- (2011) Rene Vidal IEEE SIGNAL PROCESSING MAGAZINE
- Robust principal component analysis?
- (2011) Emmanuel J. Candès et al. JOURNAL OF THE ACM
- A Singular Value Thresholding Algorithm for Matrix Completion
- (2010) Jian-Feng Cai et al. SIAM JOURNAL ON OPTIMIZATION
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