Improving generalization of double low-rank representation using Schatten-p norm

Learnable low-rank latent dictionary for subspace clustering

(2021) Yesong Xu et al.   PATTERN RECOGNITION

Low Rank Regularization: A review

(2020) Zhanxuan Hu et al.   NEURAL NETWORKS

A hierarchical weighted low-rank representation for image clustering and classification

(2020) Zhiqiang Fu et al.   PATTERN RECOGNITION

Robust Subspace Clustering With Low-Rank Structure Constraint

(2020) Feiping Nie et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Online Robust Principal Component Analysis With Change Point Detection

(2019) Wei Xiao et al.   IEEE TRANSACTIONS ON MULTIMEDIA

Adaptive Weighted Sparse Principal Component Analysis for Robust Unsupervised Feature Selection

(2019) Shuangyan Yi et al.   IEEE Transactions on Neural Networks and Learning Systems

Accurate Tensor Completion via Adaptive Low-Rank Representation

(2019) Lei Zhang et al.   IEEE Transactions on Neural Networks and Learning Systems

Subspace Clustering via Learning an Adaptive Low-Rank Graph

(2018) Ming Yin et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Low Rank Matrix Recovery via Robust Outlier Estimation

(2018) Xiaojie Guo et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

A Unified Alternating Direction Method of Multipliers by Majorization Minimization

(2018) Canyi Lu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Robust Subspace Segmentation by Self-Representation Constrained Low-Rank Representation

(2018) Lai Wei et al.   NEURAL PROCESSING LETTERS

Robust principal component analysis via optimal mean by joint ℓ 2,1 and Schatten p -norms minimization

(2018) Xiaoshuang Shi et al.   NEUROCOMPUTING

Adaptive weighted nonnegative low-rank representation

(2018) Jie Wen et al.   PATTERN RECOGNITION

Connections Between Nuclear-Norm and Frobenius-Norm-Based Representations

(2018) Xi Peng et al.   IEEE Transactions on Neural Networks and Learning Systems

Reinforced Robust Principal Component Pursuit

(2018) Pratik Prabhanjan Brahma et al.   IEEE Transactions on Neural Networks and Learning Systems

LRR for Subspace Segmentation via Tractable Schatten-$p$ Norm Minimization and Factorization

(2018) Hengmin Zhang et al.   IEEE Transactions on Cybernetics

Online Schatten quasi-norm minimization for robust principal component analysis

(2018) Xixi Jia et al.   INFORMATION SCIENCES

Matrix Completion Based on Non-Convex Low-Rank Approximation

(2018) Feiping Nie et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Robust Neighborhood Preserving Projection by Nuclear/L2,1-Norm Regularization for Image Feature Extraction

(2017) Zhao Zhang et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications

(2017) Fanhua Shang et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Learning robust and discriminative low-rank representations for face recognition with occlusion

(2017) Guangwei Gao et al.   PATTERN RECOGNITION

Robust Discriminant Regression for Feature Extraction

(2017) Zhihui Lai et al.   IEEE Transactions on Cybernetics

Laplacian Regularized Low-Rank Representation and Its Applications

(2016) Ming Yin et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Weighted Nuclear Norm Minimization and Its Applications to Low Level Vision

(2016) Shuhang Gu et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Hankel Matrix Rank Minimization with Applications to System Identification and Realization

(2013) Maryam Fazel et al.   SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS

Inductive Robust Principal Component Analysis

(2012) Bing-Kun Bao et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Robust Recovery of Subspace Structures by Low-Rank Representation

(2012) Guangcan Liu et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE