Gui-Fu Lu

IEEE Trans. Image Process., 2024

2023

Multi-view subspace similarity learning based on t-SVD.

[BibT_eX]

[DOI]

Rong Tang

Multim. Tools Appl., December, 2023

Consensus latent incomplete multi-view clustering with low-rank tensor constraint.

[BibT_eX]

[DOI]

Int. J. Mach. Learn. Cybern., November, 2023

Robust subspace clustering via multi-affinity matrices fusion.

[BibT_eX]

[DOI]

Knowl. Based Syst., October, 2023

Multi-view clustering based on a multimetric matrix fusion method.

[BibT_eX]

[DOI]

Expert Syst. Appl., October, 2023

A late fusion scheme for multi-graph regularized NMF.

[BibT_eX]

[DOI]

Mach. Vis. Appl., September, 2023

Unbalanced incomplete multi-view clustering based on low-rank tensor graph learning.

[BibT_eX]

[DOI]

Expert Syst. Appl., September, 2023

Multi-view clustering indicator learning with scaled similarity.

[BibT_eX]

[DOI]

Liang Yao

Pattern Anal. Appl., August, 2023

Mixed structure low-rank representation for multi-view subspace clustering.

[BibT_eX]

[DOI]

Appl. Intell., August, 2023

Clean affinity matrix learning with rank equality constraint for multi-view subspace clustering.

[BibT_eX]

[DOI]

Jinbiao Zhao

Pattern Recognit., 2023

High-order manifold regularized multi-view subspace clustering with robust affinity matrices and weighted TNN.

[BibT_eX]

[DOI]

Pattern Recognit., 2023

Consensus similarity learning based on tensor nuclear norm.

[BibT_eX]

[DOI]

Rong Tang

Mach. Vis. Appl., 2023

Robust and optimal neighborhood graph learning for multi-view clustering.

[BibT_eX]

[DOI]

Yangfan Du

Inf. Sci., 2023

Scalable incomplete multi-view clustering via tensor Schatten <i>p</i>-norm and tensorized bipartite graph.

[BibT_eX]

[DOI]

Bing Cai

Eng. Appl. Artif. Intell., 2023

Efficient Tensor Low-Rank Representation with a Closed Form Solution.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 7th Asian Conference, 2023

2022

Double structure scaled simplex representation for multi-view subspace clustering.

[BibT_eX]

[DOI]

Liang Yao

Neural Networks, 2022

One-step incomplete multiview clustering with low-rank tensor graph learning.

[BibT_eX]

[DOI]

Inf. Sci., 2022

Tensor subspace clustering using consensus tensor low-rank representation.

[BibT_eX]

[DOI]

Bing Cai

Inf. Sci., 2022

Clean and robust affinity matrix learning for multi-view clustering.

[BibT_eX]

[DOI]

Jinbiao Zhao

Appl. Intell., 2022

Latent multi-view self-representations for clustering via the tensor nuclear norm.

[BibT_eX]

[DOI]

Jinbiao Zhao

Appl. Intell., 2022

Robust low-rank representation with adaptive graph regularization from clean data.

[BibT_eX]

[DOI]

Ganyi Tang

Appl. Intell., 2022

Constrained Multilinear Multi-view Subspace Representation Learning for Clustering based on Tensor Nuclear Norm.

[BibT_eX]

[DOI]

Rong Tang

Proceedings of the 9th International Conference on Dependable Systems and Their Applications, 2022

Kernel Subspace Clustering based on Block Diagonal Representation and Sparse Constraints.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Dependable Systems and Their Applications, 2022

2021

δ-Norm-Based Robust Regression With Applications to Image Analysis.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2021

Multi-view subspace clustering with Kronecker-basis-representation-based tensor sparsity measure.

[BibT_eX]

[DOI]

Mach. Vis. Appl., 2021

Block Diagonal Sparse Subspace Clustering.

[BibT_eX]

[DOI]

Proceedings of the 13th International Conference on Wireless Communications and Signal Processing, 2021

Improved Non-negative Matrix Factorization Algorithm for Sparse Graph Regularization.

[BibT_eX]

[DOI]

Proceedings of the Data Science, 2021

2020

Hyper-Laplacian regularized multi-view subspace clustering with low-rank tensor constraint.

[BibT_eX]

[DOI]

Neural Networks, 2020

Using Algebra Graph Representation to Detect Pairwise-Constraint Software Faults.

[BibT_eX]

[DOI]

IEEE Access, 2020

2019

A Fast Rough Mode Decision Algorithm for HEVC.

[BibT_eX]

[DOI]

J. Inf. Process. Syst., 2019

2018

Matrix exponential based discriminant locality preserving projections for feature extraction.

[BibT_eX]

[DOI]

Neural Networks, 2018

Sparse L1-norm-based linear discriminant analysis.

[BibT_eX]

[DOI]

Multim. Tools Appl., 2018

2017

Robust Image Regression Based on the Extended Matrix Variate Power Exponential Distribution of Dependent Noise.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks Learn. Syst., 2017

L1-norm based null space discriminant analysis.

[BibT_eX]

[DOI]

Multim. Tools Appl., 2017

2016

Low-Rank Matrix Factorization With Adaptive Graph Regularizer.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2016

L1-norm-based principal component analysis with adaptive regularization.

[BibT_eX]

[DOI]

Pattern Recognit., 2016

L1-norm and maximum margin criterion based discriminant locality preserving projections via trace Lasso.

[BibT_eX]

[DOI]

Pattern Recognit., 2016

A New and Fast Implementation of Orthogonal LDA Algorithm and Its Incremental Extension.

[BibT_eX]

[DOI]

Neural Process. Lett., 2016

Graph Maximum Margin Criterion for Face Recognition.

[BibT_eX]

[DOI]

Neural Process. Lett., 2016

Generalizing intersection kernel support vector machines for color texture based recognition.

[BibT_eX]

[DOI]

J. Vis. Commun. Image Represent., 2016

Spare L1-norm-based maximum margin criterion.

[BibT_eX]

[DOI]

Ganyi Tang

J. Vis. Commun. Image Represent., 2016

2015

Incremental maximum margin criterion based on eigenvalue decomposition updating algorithm.

[BibT_eX]

[DOI]

Mach. Vis. Appl., 2015

Incremental learning from chunk data for IDR/QR.

[BibT_eX]

[DOI]

Image Vis. Comput., 2015

2013

Object recognition using Gabor co-occurrence similarity.

[BibT_eX]

[DOI]

Pattern Recognit., 2013

Complexity-reduced implementations of complete and null-space-based linear discriminant analysis.

[BibT_eX]

[DOI]

Wenming Zheng

Neural Networks, 2013

Improved complete neighbourhood preserving embedding for face recognition.

[BibT_eX]

[DOI]

IET Comput. Vis., 2013

2012

Incremental complete LDA for face recognition.

[BibT_eX]

[DOI]

Pattern Recognit., 2012

Feature Extraction Using a Complete Kernel Extension of Supervised Graph Embedding.

[BibT_eX]

[DOI]

Neural Process. Lett., 2012

Incremental learning of complete linear discriminant analysis for face recognition.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2012

Face recognition using discriminant sparsity neighborhood preserving embedding.

[BibT_eX]

[DOI]

Zhong Jin

Knowl. Based Syst., 2012

Feature extraction using a fast null space based linear discriminant analysis algorithm.

[BibT_eX]

[DOI]

Inf. Sci., 2012

Incremental learning of discriminant common vectors for feature extraction.

[BibT_eX]

[DOI]

Appl. Math. Comput., 2012

2011

Orthogonal Complete Discriminant Locality Preserving Projections for Face Recognition.

[BibT_eX]

[DOI]

Zhong Lin

Zhong Jin

Neural Process. Lett., 2011

Face recognition using multi-scale differential invariants in statistical manifold framework.

[BibT_eX]

[DOI]

Int. J. Data Min. Model. Manag., 2011

2010

Face recognition using discriminant locality preserving projections based on maximum margin criterion.

[BibT_eX]

[DOI]