Block Independent Component Analysis for Face Recognition. - Lei Zhang 006; Quanxue Gao; David Zhang 001 (ICIAP, 2007)

Is two-dimensional PCA equivalent to a special case of modular PCA? - Quanxue Gao (Pattern Recognit. Lett., 2007)

Comments on "On Image Matrix Based Feature Extraction Algorithms". - Quanxue Gao; Lei Zhang 006; David Zhang 001; Jian Yang 003 (IEEE Trans. Syst. Man Cybern. Part B, 2007)

Directional independent component analysis with tensor representation. - Lei Zhang 006; Quanxue Gao; David Zhang 001 (CVPR, 2008)

Screening Diabetic Retinopathy Through Color Retinal Images. - Qin Li 001; Xue-Min Jin; Quanxue Gao; Jane You; Prabir Bhattacharya (ICMB, 2008)

Face recognition using FLDA with single training image per person. - Quanxue Gao; Lei Zhang 006; David Zhang 001 (Appl. Math. Comput., 2008)

Sequential row-column independent component analysis for face recognition. - Quanxue Gao; Lei Zhang 006; David Zhang 001 (Neurocomputing, 2009)

Directional Multimode Subspace Analysis with Tensor Representation-Discriminant Feature Extraction. - Quanxue Gao; Jun Hou; Xiujuan Hao; Yiying Li (CASoN, 2010)

Directional Principal Component Analysis for Image Matrix. - Quanxue Gao; Yiying Li; Yamin Liu; Haijun Zhang (CASoN, 2010)

Directional Two-dimensional Neighborhood Preserving Projection for Face Recognition. - Yiying Li; Qichuan Tian; Quanxue Gao; Jing Xu (CASoN, 2010)

Two-dimensional supervised local similarity and diversity projection. - Quanxue Gao; Hui Xu; Yiying Li; De-Yan Xie (Pattern Recognit., 2010)

Independent components extraction from image matrix. - Quanxue Gao; Lei Zhang 006; David Zhang 001; Hui Xu (Pattern Recognit. Lett., 2010)

Two-dimensional margin, similarity and variation embedding. - Quanxue Gao; Haijun Zhang; Jingjing Liu (Neurocomputing, 2012)

Enhanced fisher discriminant criterion for image recognition. - Quanxue Gao; Jingjing Liu; Haijun Zhang; Jun Hou; Xiaojing Yang (Pattern Recognit., 2012)

Feature extraction using two-dimensional neighborhood margin and variation embedding. - Quanxue Gao; Xiujuan Hao; Qijun Zhao; Weiguo Shen; Jingjie Ma (Comput. Vis. Image Underst., 2013)

Joint geometry and variability for image recognition. - Quanxue Gao; Haijun Zhang; Xiaojing Yang; Jingjing Liu; Yamin Liu (Neurocomputing, 2013)

Joint Global and Local Structure Discriminant Analysis. - Quanxue Gao; Jingjing Liu; Hailin Zhang; Xinbo Gao 001; Kui Li (IEEE Trans. Inf. Forensics Secur., 2013)

Two-Dimensional Maximum Local Variation Based on Image Euclidean Distance for Face Recognition. - Quanxue Gao; Feifei Gao; Hailin Zhang 001; Xiujuan Hao; Xiaogang Wang 001 (IEEE Trans. Image Process., 2013)

Stable Orthogonal Local Discriminant Embedding for Linear Dimensionality Reduction. - Quanxue Gao; Jingjie Ma; Hailin Zhang; Xinbo Gao 001; Yamin Liu (IEEE Trans. Image Process., 2013)

Global-local fisher discriminant approach for face recognition. - Qianqian Wang 001; Xiaolei Hu; Quanxue Gao; Bing Li; Yong Wang (Neural Comput. Appl., 2014)

Stable locality sensitive discriminant analysis for image recognition. - Quanxue Gao; Jingjing Liu; Kai Cui; Hailin Zhang; Xiaogang Wang (Neural Networks, 2014)

An Accelerated Two-Step Iteration Hybrid-norm Algorithm for Image Restoration. - Yong Wang; Wenjuan Xu; Xiaoyu Yang; Qianqian Qiao; Zheng Jia; Quanxue Gao (CCCV (2), 2015)

Merging model-based two-dimensional principal component analysis. - Kai Cui; Quanxue Gao; Hailin Zhang; Xinbo Gao 001; De-Yan Xie (Neurocomputing, 2015)

A novel semi-supervised learning for face recognition. - Quanxue Gao; Yunfang Huang; Xinbo Gao 001; Weiguo Shen; Hailin Zhang (Neurocomputing, 2015)

Discriminative sparsity preserving projections for image recognition. - Quanxue Gao; Yunfang Huang; Hailin Zhang; Xin Hong; Kui Li; Yong Wang (Pattern Recognit., 2015)

Dimensionality Reduction by Integrating Sparse Representation and Fisher Criterion and its Applications. - Quanxue Gao; Qianqian Wang 001; Yunfang Huang; Xinbo Gao 001; Xin Hong; Hailin Zhang (IEEE Trans. Image Process., 2015)

Robust 2DPCA and Its Application. - Qianqian Wang 001; Quanxue Gao (CVPR Workshops, 2016)

Discriminant structure embedding for image recognition. - Shuo Miao; Jing Wang 105; Quanxue Gao; Fang Chen; Yong Wang (Neurocomputing, 2016)

On the schatten norm for matrix based subspace learning and classification. - Qianqian Wang 001; Fang Chen; Quanxue Gao; Xinbo Gao 001; Feiping Nie 001 (Neurocomputing, 2016)

Rebuttal to "Comments on 'Joint Global and Local Structure Discriminant Analysis"'. - Quanxue Gao (IEEE Trans. Inf. Forensics Secur., 2016)

Two-Dimensional PCA with F-Norm Minimization. - Qianqian Wang 001; Quanxue Gao (AAAI, 2017)

Angle Principal Component Analysis. - Qianqian Wang 001; Quanxue Gao; Xinbo Gao 001; Feiping Nie 001 (IJCAI, 2017)

Trace ratio 2DLDA with L1-norm optimization. - Mengyuan Li; Jing Wang 105; Qianqian Wang 001; Quanxue Gao (Neurocomputing, 2017)

F-norm distance metric based robust 2DPCA and face recognition. - Tao Li; Mengyuan Li; Quanxue Gao; De-Yan Xie (Neural Networks, 2017)

Optimal mean two-dimensional principal component analysis with F-norm minimization. - Qianqian Wang 001; Quanxue Gao; Xinbo Gao 001; Feiping Nie 001 (Pattern Recognit., 2017)

Adaptive maximum margin analysis for image recognition. - Qianqian Wang 001; Lan Ma; Quanxue Gao; Yunsong Li 001; Yunfang Huang; Yang Liu 084 (Pattern Recognit., 2017)

A Non-Greedy Algorithm for L1-Norm LDA. - Yang Liu 084; Quanxue Gao; Shuo Miao; Xinbo Gao 001; Feiping Nie 001; Yunsong Li 001 (IEEE Trans. Image Process., 2017)

Robust Formulation for PCA: Avoiding Mean Calculation With L2, p-norm Maximization. - Shuangli Liao; Jin Li 011; Yang Liu 069; Quanxue Gao; Xinbo Gao 001 (AAAI, 2018)

Euler Sparse Representation for Image Classification. - Yang Liu 069; Quanxue Gao; Jungong Han; Shujian Wang (AAAI, 2018)

Partial Multi-view Clustering via Consistent GAN. - Qianqian Wang 001; Zhengming Ding; Zhiqiang Tao; Quanxue Gao; Yun Fu 001 (ICDM, 2018)

Zero Shot Learning via Low-rank Embedded Semantic AutoEncoder. - Yang Liu 069; Quanxue Gao; Jin Li 011; Jungong Han; Ling Shao 001 (IJCAI, 2018)

Learning with Adaptive Neighbors for Image Clustering. - Yang Liu 069; Quanxue Gao; Zhaohua Yang; Shujian Wang (IJCAI, 2018)

L2, 1-Norm Discriminant Manifold Learning. - Yang Liu 069; Quanxue Gao; Xinbo Gao 001; Ling Shao 001 (IEEE Access, 2018)

Dimensionality reduction by LPP-L21. - Shujian Wang; De-Yan Xie; Fang Chen; Quanxue Gao (IET Comput. Vis., 2018)

Nuclear-norm based semi-supervised multiple labels learning. - Yang Liu 069; Feiping Nie 001; Quanxue Gao (Neurocomputing, 2018)

Learning more distinctive representation by enhanced PCA network. - Yang Liu 069; Shuangshuang Zhao; Qianqian Wang 001; Quanxue Gao (Neurocomputing, 2018)

Euler Label Consistent K-SVD for image classification and action recognition. - Yue Song; Yang Liu 069; Quanxue Gao; Xinbo Gao 001; Feiping Nie 001; Rongmei Cui (Neurocomputing, 2018)

SVM based multi-label learning with missing labels for image annotation. - Yang Liu 069; Kaiwen Wen; Quanxue Gao; Xinbo Gao 001; Feiping Nie 001 (Pattern Recognit., 2018)

Angle 2DPCA: A New Formulation for 2DPCA. - Quanxue Gao; Lan Ma; Yang Liu 069; Xinbo Gao 001; Feiping Nie 001 (IEEE Trans. Cybern., 2018)

Discriminant Analysis via Joint Euler Transform and ℓ2, 1-Norm. - Shuangli Liao; Quanxue Gao; Zhaohua Yang; Fang Chen; Feiping Nie 001; Jungong Han (IEEE Trans. Image Process., 2018)

ℓ2, p -Norm Based PCA for Image Recognition. - Qianqian Wang 001; Quanxue Gao; Xinbo Gao 001; Feiping Nie 001 (IEEE Trans. Image Process., 2018)

Robust DLPP With Nongreedy ℓ1-Norm Minimization and Maximization. - Qianqian Wang 001; Quanxue Gao; De-Yan Xie; Xinbo Gao 001; Yong Wang (IEEE Trans. Neural Networks Learn. Syst., 2018)

Tensor Linear Regression and Its Application to Color Face Recognition. - Quanxue Gao; Jiafeng Cheng; De-Yan Xie; Pu Zhang; Wei Xia; Qianqian Wang 001 (ICCV Workshops, 2019)

Deep Adversarial Multi-view Clustering Network. - Zhaoyang Li; Qianqian Wang 001; Zhiqiang Tao; Quanxue Gao; Zhaohua Yang (IJCAI, 2019)

Worst-Case Discriminative Feature Selection. - Shuangli Liao; Quanxue Gao; Feiping Nie 001; Yang Liu 069; Xiangdong Zhang (IJCAI, 2019)

Graph and Autoencoder Based Feature Extraction for Zero-shot Learning. - Yang Liu 069; De-Yan Xie; Quanxue Gao; Jungong Han; Shujian Wang; Xinbo Gao 001 (IJCAI, 2019)

Adaptive Semi-Supervised Classification by Joint Global and Local Graph. - Siyang Deng; Qianqian Wang 001; Quanxue Gao (IEEE Access, 2019)

Image Classification Using Low-Rank Regularized Extreme Learning Machine. - Qin Li 001; Yang Liu 069; Shujian Wang; Quanxue Gao; Xinbo Gao 001 (IEEE Access, 2019)

Multi-View Spectral Clustering via Integrating Global and Local Graphs. - De-Yan Xie; Quanxue Gao; Qianqian Wang 001; Song Xiao (IEEE Access, 2019)

Multi-View Classification via Adaptive Discriminant Analysis. - De-Yan Xie; Qin Li 001; Wei Xia; Shiwei Pang; Huihui He; Quanxue Gao (IEEE Access, 2019)

Consistent Embedded GAN for Image-to-Image Translation. - Feng Xiong; Qianqian Wang 001; Quanxue Gao (IEEE Access, 2019)

Hyperspectral image denoising via minimizing the partial sum of singular values and superpixel segmentation. - Yang Liu 069; Caifeng Shan; Quanxue Gao; Xinbo Gao 001; Jungong Han; Rongmei Cui (Neurocomputing, 2019)

Nuclear-norm based 2DLDA with application to face recognition. - Pu Zhang; Siyang Deng; Feiping Nie 001; Yang Liu 069; Xiangdong Zhang; Quanxue Gao (Neurocomputing, 2019)

Adaptive robust principal component analysis. - Yang Liu 069; Xinbo Gao 001; Quanxue Gao; Ling Shao 001; Jungong Han (Neural Networks, 2019)

Flexible unsupervised feature extraction for image classification. - Yang Liu 069; Feiping Nie 001; Quanxue Gao; Xinbo Gao 001; Jungong Han; Ling Shao 001 (Neural Networks, 2019)

${R}_1$ -2-DPCA and Face Recognition. - Quanxue Gao; Sai Xu; Fang Chen; Chris Ding; Xinbo Gao 001; Yunsong Li 001 (IEEE Trans. Cybern., 2019)

Cross-Modal Subspace Clustering via Deep Canonical Correlation Analysis. - Quanxue Gao; Huanhuan Lian; Qianqian Wang 001; Gan Sun (AAAI, 2020)

Tensor-SVD Based Graph Learning for Multi-View Subspace Clustering. - Quanxue Gao; Wei Xia; Zhizhen Wan; De-Yan Xie; Pu Zhang (AAAI, 2020)

Multi-View Attribute Graph Convolution Networks for Clustering. - Jiafeng Cheng; Qianqian Wang 001; Zhiqiang Tao; De-Yan Xie; Quanxue Gao (IJCAI, 2020)

Generative Partial Multi-View Clustering. - Qianqian Wang 001; Zhengming Ding; Zhiqiang Tao; Quanxue Gao; Yun Fu 001 (CoRR, 2020)

Fast algorithm for large-scale subspace clustering by LRR. - De-Yan Xie; Feiping Nie 001; Quanxue Gao; Song Xiao (IET Image Process., 2020)

Discriminative comparison classifier for generalized zero-shot learning. - Mingzhen Hou; Wei Xia; Xiangdong Zhang; Quanxue Gao (Neurocomputing, 2020)

Double robust principal component analysis. - Qianqian Wang 001; Quanxue Gao; Gan Sun; Chris Ding (Neurocomputing, 2020)

Multi-view clustering by joint manifold learning and tensor nuclear norm. - De-Yan Xie; Wei Xia; Qianqian Wang 001; Quanxue Gao; Song Xiao (Neurocomputing, 2020)

On the optimal solution to maximum margin projection pursuit. - De-Yan Xie; Feiping Nie 001; Quanxue Gao (Multim. Tools Appl., 2020)

Multi-view projected clustering with graph learning. - Quanxue Gao; Zhizhen Wan; Ying Liang; Qianqian Wang 001; Yang Liu 069; Ling Shao 001 (Neural Networks, 2020)

Label-activating framework for zero-shot learning. - Yang Liu 069; Xinbo Gao 001; Quanxue Gao; Jungong Han; Ling Shao 001 (Neural Networks, 2020)

Adaptive latent similarity learning for multi-view clustering. - De-Yan Xie; Quanxue Gao; Qianqian Wang 001; Xiangdong Zhang; Xinbo Gao 001 (Neural Networks, 2020)

Low-rank tensor constrained co-regularized multi-view spectral clustering. - Huiling Xu; Xiangdong Zhang; Wei Xia; Quanxue Gao; Xinbo Gao 001 (Neural Networks, 2020)

Multiview Clustering by Joint Latent Representation and Similarity Learning. - De-Yan Xie; Xiangdong Zhang; Quanxue Gao; Jiale Han 001; Song Xiao; Xinbo Gao 001 (IEEE Trans. Cybern., 2020)

Deep Self-Supervised t-SNE for Multi-modal Subspace Clustering. - Qianqian Wang 001; Wei Xia; Zhiqiang Tao; Quanxue Gao; Xiaochun Cao (ACM Multimedia, 2021)

Multiple Graph Learning for Scalable Multi-view Clustering. - Tianyu Jiang; Quanxue Gao (CoRR, 2021)

Effective and Efficient Graph Learning for Multi-view Clustering. - Quanxue Gao; Wei Xia; Xinbo Gao 001; Dacheng Tao (CoRR, 2021)

Self-supervised Contrastive Attributed Graph Clustering. - Wei Xia; Quanxue Gao; Ming Yang 024; Xinbo Gao 001 (CoRR, 2021)

Self-representation and matrix factorization based multi-view clustering. - Ying Dou; Yu Yun; Quanxue Gao; Xiangdong Zhang (Neurocomputing, 2021)

Self-supervised graph convolutional clustering by preserving latent distribution. - Shiwen Kou; Wei Xia; Xiangdong Zhang; Quanxue Gao; Xinbo Gao 001 (Neurocomputing, 2021)

Multi-view clustering by joint spectral embedding and spectral rotation. - Zhizhen Wan; Huiling Xu; Quanxue Gao (Neurocomputing, 2021)

Regression-based clustering network via combining prior information. - Wei Xia; Quanxue Gao; Qianqian Wang 001; Xinbo Gao 001 (Neurocomputing, 2021)

Adversarial self-supervised clustering with cluster-specificity distribution. - Wei Xia; Xiangdong Zhang; Quanxue Gao; Xinbo Gao 001 (Neurocomputing, 2021)

Self-representation and Class-Specificity Distribution Based Multi-View Clustering. - Yu Yun; Wei Xia; Yongqing Zhang; Quanxue Gao; Xinbo Gao 001 (Neurocomputing, 2021)

Multiple graphs learning with a new weighted tensor nuclear norm. - De-Yan Xie; Quanxue Gao; Siyang Deng; Xiaojun Yang; Xinbo Gao 001 (Neural Networks, 2021)

Graph embedding clustering: Graph attention auto-encoder with cluster-specificity distribution. - Huiling Xu; Wei Xia; Quanxue Gao; Jungong Han; Xinbo Gao 001 (Neural Networks, 2021)

Enhanced Tensor RPCA and its Application. - Quanxue Gao; Pu Zhang; Wei Xia; De-Yan Xie; Xinbo Gao 001; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Cross-view classification by joint adversarial learning and class-specificity distribution. - Siyang Deng; Wei Xia; Quanxue Gao; Xinbo Gao 001 (Pattern Recognit., 2021)

Relation-based Discriminative Cooperation Network for Zero-Shot Classification. - Yang Liu 069; Xinbo Gao 001; Quanxue Gao; Jungong Han; Ling Shao 001 (Pattern Recognit., 2021)

Satellite-Borne Optical Remote Sensing Image Registration Based on Point Features. - Xinan Hou; Quanxue Gao; Rong Wang; Xin Luo 008 (Sensors, 2021)

Generative Partial Multi-View Clustering With Adaptive Fusion and Cycle Consistency. - Qianqian Wang 001; Zhengming Ding; Zhiqiang Tao; Quanxue Gao; Yun Fu 001 (IEEE Trans. Image Process., 2021)

Adversarial Multi-Path Residual Network for Image Super-Resolution. - Qianqian Wang 001; Quanxue Gao; Linlu Wu; Gan Sun; Licheng Jiao (IEEE Trans. Image Process., 2021)

iCmSC: Incomplete Cross-Modal Subspace Clustering. - Qianqian Wang 001; Huanhuan Lian; Gan Sun; Quanxue Gao; Licheng Jiao (IEEE Trans. Image Process., 2021)

Deep Multi-View Subspace Clustering With Unified and Discriminative Learning. - Qianqian Wang 001; Jiafeng Cheng; Quanxue Gao; Guoshuai Zhao; Licheng Jiao (IEEE Trans. Multim., 2021)

A multi-view clustering framework via integrating K-means and graph-cut. - Han Lu; Quanxue Gao; Xiangdong Zhang; Wei Xia (Neurocomputing, 2022)

Contrastive deep embedded clustering. - Guoshuai Sheng; Qianqian Wang 001; Chengquan Pei; Quanxue Gao (Neurocomputing, 2022)

Multi-view Spectral Clustering with Adaptive Graph Learning and Tensor Schatten p-norm. - Yujiao Zhao; Yu Yun; Xiangdong Zhang; Qin Li; Quanxue Gao (Neurocomputing, 2022)

Low-rank constraint bipartite graph learning. - Qian Zhou; Haizhou Yang; Quanxue Gao (Neurocomputing, 2022)

Fast multiple graphs learning for multi-view clustering. - Tianyu Jiang; Quanxue Gao (Neural Networks, 2022)

Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation. - Wei Xia; Sen Wang; Ming Yang 024; Quanxue Gao; Jungong Han; Xinbo Gao 001 (Neural Networks, 2022)

Attributes learning network for generalized zero-shot learning. - Yu Yun; Sen Wang; Mingzhen Hou; Quanxue Gao (Neural Networks, 2022)

Enhanced nuclear norm based matrix regression for occluded face recognition. - Qin Li 001; Huihui He; Hong Lai; Tie Cai; Qianqian Wang 001; Quanxue Gao (Pattern Recognit., 2022)

Semi-Supervised Clustering via Cannot Link Relationship for Multiview Data. - Zhaorui Zhu; Quanxue Gao (IEEE Trans. Circuits Syst. Video Technol., 2022)

Tensor Completion-Based Incomplete Multiview Clustering. - Wei Xia; Quanxue Gao; Qianqian Wang 001; Xinbo Gao 001 (IEEE Trans. Cybern., 2022)

Multiview Subspace Clustering by an Enhanced Tensor Nuclear Norm. - Wei Xia; Xiangdong Zhang; Quanxue Gao; Xiaochuang Shu; Jungong Han; Xinbo Gao 001 (IEEE Trans. Cybern., 2022)

View-Consistency Learning for Incomplete Multiview Clustering. - Ziyu Lv; Quanxue Gao; Xiangdong Zhang; Qin Li 001; Ming Yang 024 (IEEE Trans. Image Process., 2022)

Multiview Spectral Clustering With Bipartite Graph. - Haizhou Yang; Quanxue Gao; Wei Xia; Ming Yang 024; Xinbo Gao 001 (IEEE Trans. Image Process., 2022)

Zero-Shot Learning Based on Quality-Verifying Adversarial Network. - Siyang Deng; Gang Xiang; Quanxue Gao; Wei Xia; Xinbo Gao 001 (IEEE Trans. Multim., 2022)

Self-Supervised Graph Convolutional Network for Multi-View Clustering. - Wei Xia; Qianqian Wang 001; Quanxue Gao; Xiangdong Zhang; Xinbo Gao 001 (IEEE Trans. Multim., 2022)

Centerless Multi-View K-means Based on the Adjacency Matrix. - Han Lu; Quanxue Gao; Qianqian Wang 001; Ming Yang 024; Wei Xia (AAAI, 2023)

Capped L2p-Norm Based 2DPCA with Adaptive Capped Threshold Learning for Image Processing. - Meiling Liu; Wei Feng 010; Chengquan Pei; Qianqian Wang 001; Quanxue Gao (ICCT, 2023)

Dropping Pathways Towards Deep Multi-View Graph Subspace Clustering Networks. - Zihao Zhang; Qianqian Wang 001; Zhiqiang Tao; Quanxue Gao; Wei Feng 010 (ACM Multimedia, 2023)

Orthogonal Non-negative Tensor Factorization based Multi-view Clustering. - Jing Li 026; Quanxue Gao; Qianqian Wang 001; Ming Yang 024; Wei Xia (NeurIPS, 2023)

Multi-View Clustering via Semi-non-negative Tensor Factorization. - Jing Li 026; Quanxue Gao; Qianqian Wang 001; Wei Xia; Xinbo Gao 001 (CoRR, 2023)

Rethinking k-means from manifold learning perspective. - Quanxue Gao; Qianqian Wang 001; Han Lu; Wei Xia; Xinbo Gao 001 (CoRR, 2023)

Multi-modal object detection via transformer network. - Wenbing Liu; Haibo Wang; Quanxue Gao; Zhaorui Zhu (IET Image Process., 2023)

Graph Embedding Contrastive Multi-Modal Representation Learning for Clustering. - Wei Xia; Tianxiu Wang; Quanxue Gao; Ming Yang 024; Xinbo Gao 001 (IEEE Trans. Image Process., 2023)

Self-Weighted Anchor Graph Learning for Multi-View Clustering. - Xiaochuang Shu; Xiangdong Zhang; Quanxue Gao; Ming Yang 024; Rong Wang 001; Xinbo Gao 001 (IEEE Trans. Multim., 2023)

Self-Consistent Contrastive Attributed Graph Clustering With Pseudo-Label Prompt. - Wei Xia; Qianqian Wang 001; Quanxue Gao; Ming Yang 024; Xinbo Gao 001 (IEEE Trans. Multim., 2023)

Enhanced tensor low-rank representation learning for multi-view clustering. - De-Yan Xie; Quanxue Gao; Ming Yang (Neural Networks, 2023)

Tensorized Bipartite Graph Learning for Multi-View Clustering. - Wei Xia; Quanxue Gao; Qianqian Wang 001; Xinbo Gao 001; Chris Ding; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Joint feature selection and optimal bipartite graph learning for subspace clustering. - Shikun Mei; Wenhui Zhao; Quanxue Gao; Ming Yang 024; Xinbo Gao 001 (Neural Networks, 2023)

Low-rank discrete multi-view spectral clustering. - Yu Yun; Jing Li 026; Quanxue Gao; Ming Yang 024; Xinbo Gao 001 (Neural Networks, 2023)

Active learning based on similarity level histogram and adaptive-scale sampling for very high resolution image classification. - Guangfei Li; Quanxue Gao; Ming Yang 024; Xinbo Gao 001 (Neural Networks, 2023)

Contrastive self-representation learning for data clustering. - Wenhui Zhao; Quanxue Gao; Shikun Mei; Ming Yang 024 (Neural Networks, 2023)

Sparse discriminant PCA based on contrastive learning and class-specificity distribution. - Qian Zhou; Quanxue Gao; Qianqian Wang 001; Ming Yang 024; Xinbo Gao 001 (Neural Networks, 2023)

Adversarial Multiview Clustering Networks With Adaptive Fusion. - Qianqian Wang 001; Zhiqiang Tao; Wei Xia; Quanxue Gao; Xiaochun Cao; Licheng Jiao (IEEE Trans. Neural Networks Learn. Syst., 2023)

Partial Multi-View Clustering via Self-Supervised Network. - Wei Feng 010; Guoshuai Sheng; Qianqian Wang 001; Quanxue Gao; Zhiqiang Tao; Bo Dong 001 (AAAI, 2024)

Tensorized Label Learning on Anchor Graph. - Jing Li 026; Quanxue Gao; Qianqian Wang 001; Wei Xia (AAAI, 2024)

Embedded Feature Selection on Graph-Based Multi-View Clustering. - Wenhui Zhao; Guangfei Li; Haizhou Yang; Quanxue Gao; Qianqian Wang 001 (AAAI, 2024)

Reconstruction Weighting Principal Component Analysis with Fusion Contrastive Learning. - Qianqian Wang 001; Meiling Liu; Wei Feng 010; Mengping Jiang; Haiming Xu; Quanxue Gao (IJCAI, 2024)

Federated Multi-View Clustering via Tensor Factorization. - Wei Feng 010; Zhenwei Wu; Qianqian Wang 001; Bo Dong 001; Zhiqiang Tao; Quanxue Gao (IJCAI, 2024)

Efficient Federated Multi-View Clustering with Integrated Matrix Factorization and K-Means. - Wei Feng 010; Zhenwei Wu; Qianqian Wang 001; Bo Dong 001; Zhiqiang Tao; Quanxue Gao (IJCAI, 2024)

Label Learning Method Based on Tensor Projection. - Jing Li 026; Quanxue Gao; Qianqian Wang 001; Cheng Deng; De-Yan Xie (KDD, 2024)

Multi-View Clustering Based on Deep Non-negative Tensor Factorization. - Wei Feng 010; Dongyuan Wei; Qianqian Wang 001; Bo Dong 001; Quanxue Gao (ACM Multimedia, 2024)

Federated Fuzzy C-means with Schatten-p Norm Minimization. - Wei Feng 010; Zhenwei Wu; Qianqian Wang 001; Bo Dong 001; Quanxue Gao (ACM Multimedia, 2024)

DFMVC: Deep Fair Multi-view Clustering. - Bowen Zhao; Qianqian Wang 001; Zhiqiang Tao; Wei Feng 010; Quanxue Gao (ACM Multimedia, 2024)

One-Step Multi-View Clustering Based on Transition Probability. - Wenhui Zhao; Quanxue Gao; Guangfei Li; Cheng Deng; Ming Yang (CoRR, 2024)

Interpretable Multi-View Clustering Based on Anchor Graph Tensor Factorization. - Jing Li 026; Quanxue Gao; Cheng Deng; Qianqian Wang 001; Ming Yang 024 (CoRR, 2024)

Fuzzy K-Means Clustering without Cluster Centroids. - Han Lu; Fangfang Li 005; Quanxue Gao; Cheng Deng; Chris Ding; Qianqian Wang 001 (CoRR, 2024)

High-Discriminative Attribute Feature Learning for Generalized Zero-Shot Learning. - Yu Lei; Guoshuai Sheng; Fangfang Li; Quanxue Gao; Cheng Deng; Qin Li (CoRR, 2024)

Self-Supervised Graph Embedding Clustering. - Fangfang Li; Quanxue Gao; Ming Yang; Cheng Deng; Wei Xia (CoRR, 2024)

Dual contrastive learning for multi-view clustering. - Yichen Bao; Wenhui Zhao; Qin Zhao; Quanxue Gao; Ming Yang 024 (Neurocomputing, 2024)

Anchor graph-based multiview spectral clustering. - Yu Lei; Zuoyuan Niu; Qianqian Wang 001; Quanxue Gao; Ming Yang 024 (Neurocomputing, 2024)

Deep contrastive representation learning for multi-modal clustering. - Yang Lu; Qin Li; Xiangdong Zhang; Quanxue Gao (Neurocomputing, 2024)

Deep cross-modal subspace clustering with Contrastive Neighbour Embedding. - Zihao Zhang; Qianqian Wang 001; Chengquan Pei; Quanxue Gao (Neurocomputing, 2024)

Learning deep representation and discriminative features for clustering of multi-layer networks. - Wenming Wu; Xiaoke Ma 001; Quan Wang 006; Maoguo Gong; Quanxue Gao (Neural Networks, 2024)

Consistent graph learning for multi-view spectral clustering. - De-Yan Xie; Quanxue Gao; Yougang Zhao; Fan Yang; Wei Song (Pattern Recognit., 2024)

Non-convex tensorial multi-view clustering by integrating ℓ1-based sliced-Laplacian regularization and ℓ2,p-sparsity. - De-Yan Xie; Ming Yang 024; Quanxue Gao; Wei Song (Pattern Recognit., 2024)

Self-Supervised Edge Perceptual Learning Framework for High-Resolution Remote Sensing Images Classification. - Guangfei Li; Wenbing Liu; Quanxue Gao; Qianqian Wang 001; Jungong Han; Xinbo Gao 001 (IEEE Trans. Circuits Syst. Video Technol., 2024)

Efficient Multi-View -Means for Image Clustering. - Han Lu; Huafu Xu; Qianqian Wang 001; Quanxue Gao; Ming Yang 024; Xinbo Gao 001 (IEEE Trans. Image Process., 2024)

Unsupervised Discriminative Feature Selection via Contrastive Graph Learning. - Qian Zhou; Qianqian Wang 001; Quanxue Gao; Ming Yang 024; Xinbo Gao 001 (IEEE Trans. Image Process., 2024)

Efficient Anchor Graph Factorization for Multi-View Clustering. - Jing Li 026; Qianqian Wang 001; Ming Yang 024; Quanxue Gao; Xinbo Gao 001 (IEEE Trans. Multim., 2024)

Anchor Graph-Based Feature Selection for One-Step Multi-View Clustering. - Wenhui Zhao; Qin Li 001; Huafu Xu; Quanxue Gao; Qianqian Wang 001; Xinbo Gao 001 (IEEE Trans. Multim., 2024)

Multi-View Subspace Clustering via Structured Multi-Pathway Network. - Qianqian Wang 001; Zhiqiang Tao; Quanxue Gao; Licheng Jiao (IEEE Trans. Neural Networks Learn. Syst., 2024)

A Coarse-to-Fine Cell Division Approach for Hyperspectral Remote Sensing Image Classification. - Guangfei Li; Quanxue Gao; Jungong Han; Xinbo Gao 001 (IEEE Trans. Circuits Syst. Video Technol., 2024)

Unsupervised Cross-View Subspace Clustering via Adaptive Contrastive Learning. - Zihao Zhang; Qianqian Wang 001; Quanxue Gao; Chengquan Pei; Wei Feng 010 (IEEE Trans. Big Data, 2024)

Deep Multi-modal Graph Clustering via Graph Transformer Network. - Qianqian Wang 001; Haiming Xu; Zihao Zhang; Wei Feng 010; Quanxue Gao (AAAI, 2025)

Contrastive Multi-view Subspace Clustering via Tensor Transformers Autoencoder. - Qianqian Wang 001; Zihao Zhang; Wei Feng 010; Zhiqiang Tao; Quanxue Gao (AAAI, 2025)

Tensorized Label Learning Based Fast Fuzzy Clustering. - Xingyu Xue; Jingjing Xue; Quanxue Gao; Qianqian Wang 001 (AAAI, 2025)

Deep Fair Multi-View Clustering with Attention KAN. - Haiming Xu; Qianqian Wang 001; Boyue Wang; Quanxue Gao (CVPR, 2025)

Attribute-Missing Multi-view Graph Clustering. - Bowen Zhao; Qianqian Wang 001; Zhengming Ding; Quanxue Gao (CVPR, 2025)

Fast discrete multi-view collaborative clustering induced by label propagation. - Jin Chen; Guangyu Yang; Jingjing Xue; Quanxue Gao; Cheng Deng (Expert Syst. Appl., 2025)

A transformer-based dual contrastive learning approach for zero-shot learning. - Yu Lei; Ran Jing; Fangfang Li; Quanxue Gao; Cheng Deng (Neurocomputing, 2025)

One-step multi-view clustering via label transmission and fusion. - Wenhui Zhao; Sen Wang; Guangfei Li; Quanxue Gao; Cheng Deng (Neurocomputing, 2025)

Incomplete multi-view clustering based on hypergraph. - Jin Chen; Huafu Xu; Jingjing Xue; Quanxue Gao; Cheng Deng; Ziyu Lv (Inf. Fusion, 2025)

Multi-view clustering based on feature selection and semi-non-negative anchor graph factorization. - Shikun Mei; Qianqian Wang 001; Quanxue Gao; Ming Yang 024 (Neural Networks, 2025)

Centroid-Free K-Means With Balanced Clustering. - Bin Meng; Fangfang Li; Fan Yang 111; Quanxue Gao (IEEE Signal Process. Lett., 2025)

Image Clustering With Transition Probabilities Learning. - Xingyu Xue; Wenhui Zhao; Quanxue Gao; Ming Yang 024; Cheng Deng (IEEE Trans. Image Process., 2025)

Manifold Clustering with Schatten p-norm Maximization. - Fangfang Li; Quanxue Gao (CoRR, 2025)

Manifold Based Multi-View K-Means. - Quanxue Gao; Fangfang Li 005; Qianqian Wang 001; Xinbo Gao 001; Dacheng Tao (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Tensorized Tri-Factor Decomposition for Multi-View Clustering. - Rui Wang; Quanxue Gao; Ming Yang 024; Qianqian Wang 001 (IEEE Trans. Circuits Syst. Video Technol., 2025)

Tensorized Soft Label Learning Based on Orthogonal NMF. - Fangfang Li 005; Quanxue Gao; Qianqian Wang 001; Ming Yang 024; Cheng Deng (IEEE Trans. Neural Networks Learn. Syst., 2025)