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2020 – today
- 2025
[j116]Jin Chen, Huafu Xu, Jingjing Xue
, Quanxue Gao, Cheng Deng, Ziyu Lv:
Incomplete multi-view clustering based on hypergraph. Inf. Fusion 117: 102804 (2025)- 2024
- [j115]Zihao Zhang, Qianqian Wang, Chengquan Pei, Quanxue Gao:
Deep cross-modal subspace clustering with Contrastive Neighbour Embedding. Neurocomputing 576: 127318 (2024) - [j114]Yang Lu, Qin Li, Xiangdong Zhang, Quanxue Gao:
Deep contrastive representation learning for multi-modal clustering. Neurocomputing 581: 127523 (2024) - [j113]Yu Lei, Zuoyuan Niu, Qianqian Wang, Quanxue Gao, Ming Yang:
Anchor graph-based multiview spectral clustering. Neurocomputing 583: 127579 (2024) - [j112]Yichen Bao, Wenhui Zhao, Qin Zhao, Quanxue Gao, Ming Yang:
Dual contrastive learning for multi-view clustering. Neurocomputing 599: 128093 (2024) - [j111]Wenming Wu, Xiaoke Ma, Quan Wang, Maoguo Gong, Quanxue Gao:
Learning deep representation and discriminative features for clustering of multi-layer networks. Neural Networks 170: 405-416 (2024) - [j110]De-Yan Xie, Quanxue Gao, Yougang Zhao, Fan Yang, Wei Song:
Consistent graph learning for multi-view spectral clustering. Pattern Recognit. 154: 110598 (2024) - [j109]De-Yan Xie, Ming Yang, Quanxue Gao, Wei Song:
Non-convex tensorial multi-view clustering by integrating ℓ1-based sliced-Laplacian regularization and ℓ2,p-sparsity. Pattern Recognit. 154: 110605 (2024) - [j108]Zihao Zhang, Qianqian Wang, Quanxue Gao, Chengquan Pei, Wei Feng:
Unsupervised Cross-View Subspace Clustering via Adaptive Contrastive Learning. IEEE Trans. Big Data 10(5): 609-619 (2024) - [j107]Guangfei Li, Quanxue Gao, Jungong Han, Xinbo Gao:
A Coarse-to-Fine Cell Division Approach for Hyperspectral Remote Sensing Image Classification. IEEE Trans. Circuits Syst. Video Technol. 34(6): 4928-4941 (2024) - [j106]Guangfei Li, Wenbing Liu, Quanxue Gao, Qianqian Wang, Jungong Han, Xinbo Gao:
Self-Supervised Edge Perceptual Learning Framework for High-Resolution Remote Sensing Images Classification. IEEE Trans. Circuits Syst. Video Technol. 34(7): 6024-6038 (2024) - [j105]Han Lu, Huafu Xu, Qianqian Wang, Quanxue Gao, Ming Yang, Xinbo Gao:
Efficient Multi-View -Means for Image Clustering. IEEE Trans. Image Process. 33: 273-284 (2024) - [j104]Qian Zhou, Qianqian Wang, Quanxue Gao, Ming Yang, Xinbo Gao:
Unsupervised Discriminative Feature Selection via Contrastive Graph Learning. IEEE Trans. Image Process. 33: 972-986 (2024) - [j103]Jing Li, Qianqian Wang, Ming Yang, Quanxue Gao, Xinbo Gao:
Efficient Anchor Graph Factorization for Multi-View Clustering. IEEE Trans. Multim. 26: 5834-5845 (2024) - [j102]Wenhui Zhao, Qin Li, Huafu Xu, Quanxue Gao, Qianqian Wang, Xinbo Gao:
Anchor Graph-Based Feature Selection for One-Step Multi-View Clustering. IEEE Trans. Multim. 26: 7413-7425 (2024) - [j101]Qianqian Wang, Zhiqiang Tao, Quanxue Gao, Licheng Jiao:
Multi-View Subspace Clustering via Structured Multi-Pathway Network. IEEE Trans. Neural Networks Learn. Syst. 35(5): 7244-7250 (2024) - [c37]Wei Feng, Guoshuai Sheng, Qianqian Wang, Quanxue Gao, Zhiqiang Tao, Bo Dong:
Partial Multi-View Clustering via Self-Supervised Network. AAAI 2024: 11988-11995 - [c36]Jing Li, Quanxue Gao, Qianqian Wang, Wei Xia:
Tensorized Label Learning on Anchor Graph. AAAI 2024: 13537-13544 - [c35]Wenhui Zhao, Guangfei Li, Haizhou Yang, Quanxue Gao, Qianqian Wang:
Embedded Feature Selection on Graph-Based Multi-View Clustering. AAAI 2024: 17016-17023 - [c34]Wei Feng, Zhenwei Wu, Qianqian Wang, Bo Dong, Zhiqiang Tao, Quanxue Gao:
Federated Multi-View Clustering via Tensor Factorization. IJCAI 2024: 3962-3970 - [c33]Wei Feng, Zhenwei Wu, Qianqian Wang, Bo Dong, Zhiqiang Tao, Quanxue Gao:
Efficient Federated Multi-View Clustering with Integrated Matrix Factorization and K-Means. IJCAI 2024: 3971-3979 - [c32]Qianqian Wang, Meiling Liu, Wei Feng, Mengping Jiang, Haiming Xu, Quanxue Gao:
Reconstruction Weighting Principal Component Analysis with Fusion Contrastive Learning. IJCAI 2024: 5091-5098 - [c31]Jing Li, Quanxue Gao, Qianqian Wang, Cheng Deng, De-Yan Xie:
Label Learning Method Based on Tensor Projection. KDD 2024: 1599-1609 - [c30]Wei Feng, Dongyuan Wei, Qianqian Wang, Bo Dong, Quanxue Gao:
Multi-View Clustering Based on Deep Non-negative Tensor Factorization. ACM Multimedia 2024: 1130-1138 - [c29]Bowen Zhao, Qianqian Wang, Zhiqiang Tao, Wei Feng, Quanxue Gao:
DFMVC: Deep Fair Multi-view Clustering. ACM Multimedia 2024: 8090-8099 - [c28]Wei Feng, Zhenwei Wu, Qianqian Wang, Bo Dong, Quanxue Gao:
Federated Fuzzy C-means with Schatten-p Norm Minimization. ACM Multimedia 2024: 9407-9416 - [i12]Jing Li, Quanxue Gao, Qianqian Wang, Cheng Deng, De-Yan Xie:
Label Learning Method Based on Tensor Projection. CoRR abs/2402.16544 (2024) - [i11]Wenhui Zhao, Quanxue Gao, Guangfei Li, Cheng Deng, Ming Yang:
One-Step Multi-View Clustering Based on Transition Probability. CoRR abs/2403.01460 (2024) - [i10]Jing Li, Quanxue Gao, Cheng Deng, Qianqian Wang, Ming Yang:
Interpretable Multi-View Clustering Based on Anchor Graph Tensor Factorization. CoRR abs/2404.00883 (2024) - [i9]Han Lu, Fangfang Li, Quanxue Gao, Cheng Deng, Chris Ding, Qianqian Wang:
Fuzzy K-Means Clustering without Cluster Centroids. CoRR abs/2404.04940 (2024) - [i8]Yu Lei, Guoshuai Sheng, Fangfang Li, Quanxue Gao, Cheng Deng, Qin Li:
High-Discriminative Attribute Feature Learning for Generalized Zero-Shot Learning. CoRR abs/2404.04953 (2024) - [i7]Fangfang Li, Quanxue Gao, Ming Yang, Cheng Deng, Wei Xia:
Self-Supervised Graph Embedding Clustering. CoRR abs/2409.15887 (2024) - 2023
- [j100]Wenbing Liu, Haibo Wang, Quanxue Gao, Zhaorui Zhu:
Multi-modal object detection via transformer network. IET Image Process. 17(12): 3541-3550 (2023) - [j99]De-Yan Xie, Quanxue Gao, Ming Yang:
Enhanced tensor low-rank representation learning for multi-view clustering. Neural Networks 161: 93-104 (2023) - [j98]Shikun Mei, Wenhui Zhao, Quanxue Gao, Ming Yang, Xinbo Gao:
Joint feature selection and optimal bipartite graph learning for subspace clustering. Neural Networks 164: 408-418 (2023) - [j97]Yu Yun, Jing Li, Quanxue Gao, Ming Yang, Xinbo Gao:
Low-rank discrete multi-view spectral clustering. Neural Networks 166: 137-147 (2023) - [j96]Guangfei Li, Quanxue Gao, Ming Yang, Xinbo Gao:
Active learning based on similarity level histogram and adaptive-scale sampling for very high resolution image classification. Neural Networks 167: 22-35 (2023) - [j95]Wenhui Zhao, Quanxue Gao, Shikun Mei, Ming Yang:
Contrastive self-representation learning for data clustering. Neural Networks 167: 648-655 (2023) - [j94]Qian Zhou, Quanxue Gao, Qianqian Wang, Ming Yang, Xinbo Gao:
Sparse discriminant PCA based on contrastive learning and class-specificity distribution. Neural Networks 167: 775-786 (2023) - [j93]Wei Xia, Quanxue Gao, Qianqian Wang, Xinbo Gao, Chris Ding, Dacheng Tao:
Tensorized Bipartite Graph Learning for Multi-View Clustering. IEEE Trans. Pattern Anal. Mach. Intell. 45(4): 5187-5202 (2023) - [j92]Wei Xia, Tianxiu Wang, Quanxue Gao, Ming Yang, Xinbo Gao:
Graph Embedding Contrastive Multi-Modal Representation Learning for Clustering. IEEE Trans. Image Process. 32: 1170-1183 (2023) - [j91]Xiaochuang Shu, Xiangdong Zhang, Quanxue Gao, Ming Yang, Rong Wang, Xinbo Gao:
Self-Weighted Anchor Graph Learning for Multi-View Clustering. IEEE Trans. Multim. 25: 5485-5499 (2023) - [j90]Wei Xia, Qianqian Wang, Quanxue Gao, Ming Yang, Xinbo Gao:
Self-Consistent Contrastive Attributed Graph Clustering With Pseudo-Label Prompt. IEEE Trans. Multim. 25: 6665-6677 (2023) - [j89]Qianqian Wang, Zhiqiang Tao, Wei Xia, Quanxue Gao, Xiaochun Cao, Licheng Jiao:
Adversarial Multiview Clustering Networks With Adaptive Fusion. IEEE Trans. Neural Networks Learn. Syst. 34(10): 7635-7647 (2023) - [c27]Han Lu, Quanxue Gao, Qianqian Wang, Ming Yang, Wei Xia:
Centerless Multi-View K-means Based on the Adjacency Matrix. AAAI 2023: 8949-8956 - [c26]Meiling Liu, Wei Feng, Chengquan Pei, Qianqian Wang, Quanxue Gao:
Capped L2p-Norm Based 2DPCA with Adaptive Capped Threshold Learning for Image Processing. ICCT 2023: 665-672 - [c25]Zihao Zhang, Qianqian Wang, Zhiqiang Tao, Quanxue Gao, Wei Feng:
Dropping Pathways Towards Deep Multi-View Graph Subspace Clustering Networks. ACM Multimedia 2023: 3259-3267 - [c24]Jing Li, Quanxue Gao, Qianqian Wang, Ming Yang, Wei Xia:
Orthogonal Non-negative Tensor Factorization based Multi-view Clustering. NeurIPS 2023 - [i6]Jing Li, Quanxue Gao, Qianqian Wang, Wei Xia, Xinbo Gao:
Multi-View Clustering via Semi-non-negative Tensor Factorization. CoRR abs/2303.16748 (2023) - [i5]Quanxue Gao, Qianqian Wang, Han Lu, Wei Xia, Xinbo Gao:
Rethinking k-means from manifold learning perspective. CoRR abs/2305.07213 (2023) - 2022
- [j88]Yujiao Zhao, Yu Yun, Xiangdong Zhang, Qin Li, Quanxue Gao:
Multi-view Spectral Clustering with Adaptive Graph Learning and Tensor Schatten p-norm. Neurocomputing 468: 257-264 (2022) - [j87]Han Lu, Quanxue Gao, Xiangdong Zhang, Wei Xia:
A multi-view clustering framework via integrating K-means and graph-cut. Neurocomputing 501: 609-617 (2022) - [j86]Qian Zhou, Haizhou Yang, Quanxue Gao:
Low-rank constraint bipartite graph learning. Neurocomputing 511: 426-436 (2022) - [j85]Guoshuai Sheng, Qianqian Wang, Chengquan Pei, Quanxue Gao:
Contrastive deep embedded clustering. Neurocomputing 514: 13-20 (2022) - [j84]Wei Xia, Sen Wang, Ming Yang, Quanxue Gao, Jungong Han, Xinbo Gao:
Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation. Neural Networks 145: 1-9 (2022) - [j83]Yu Yun, Sen Wang, Mingzhen Hou, Quanxue Gao:
Attributes learning network for generalized zero-shot learning. Neural Networks 150: 112-118 (2022) - [j82]Tianyu Jiang, Quanxue Gao:
Fast multiple graphs learning for multi-view clustering. Neural Networks 155: 348-359 (2022) - [j81]Qin Li, Huihui He, Hong Lai, Tie Cai, Qianqian Wang, Quanxue Gao:
Enhanced nuclear norm based matrix regression for occluded face recognition. Pattern Recognit. 126: 108585 (2022) - [j80]Zhaorui Zhu, Quanxue Gao:
Semi-Supervised Clustering via Cannot Link Relationship for Multiview Data. IEEE Trans. Circuits Syst. Video Technol. 32(12): 8744-8755 (2022) - [j79]Wei Xia, Xiangdong Zhang, Quanxue Gao, Xiaochuang Shu, Jungong Han, Xinbo Gao:
Multiview Subspace Clustering by an Enhanced Tensor Nuclear Norm. IEEE Trans. Cybern. 52(9): 8962-8975 (2022) - [j78]Wei Xia, Quanxue Gao, Qianqian Wang, Xinbo Gao:
Tensor Completion-Based Incomplete Multiview Clustering. IEEE Trans. Cybern. 52(12): 13635-13644 (2022) - [j77]Haizhou Yang, Quanxue Gao, Wei Xia, Ming Yang, Xinbo Gao:
Multiview Spectral Clustering With Bipartite Graph. IEEE Trans. Image Process. 31: 3591-3605 (2022) - [j76]Ziyu Lv, Quanxue Gao, Xiangdong Zhang, Qin Li, Ming Yang:
View-Consistency Learning for Incomplete Multiview Clustering. IEEE Trans. Image Process. 31: 4790-4802 (2022) - [j75]Wei Xia, Qianqian Wang, Quanxue Gao, Xiangdong Zhang, Xinbo Gao:
Self-Supervised Graph Convolutional Network for Multi-View Clustering. IEEE Trans. Multim. 24: 3182-3192 (2022) - [j74]Siyang Deng, Gang Xiang, Quanxue Gao, Wei Xia, Xinbo Gao:
Zero-Shot Learning Based on Quality-Verifying Adversarial Network. IEEE Trans. Multim. 24: 4526-4537 (2022) - 2021
- [j73]Yu Yun, Wei Xia, Yongqing Zhang, Quanxue Gao, Xinbo Gao:
Self-representation and Class-Specificity Distribution Based Multi-View Clustering. Neurocomputing 437: 9-20 (2021) - [j72]Shiwen Kou, Wei Xia, Xiangdong Zhang, Quanxue Gao, Xinbo Gao:
Self-supervised graph convolutional clustering by preserving latent distribution. Neurocomputing 437: 218-226 (2021) - [j71]Wei Xia, Quanxue Gao, Qianqian Wang, Xinbo Gao:
Regression-based clustering network via combining prior information. Neurocomputing 448: 324-332 (2021) - [j70]Wei Xia, Xiangdong Zhang, Quanxue Gao, Xinbo Gao:
Adversarial self-supervised clustering with cluster-specificity distribution. Neurocomputing 449: 38-47 (2021) - [j69]Ying Dou, Yu Yun, Quanxue Gao, Xiangdong Zhang:
Self-representation and matrix factorization based multi-view clustering. Neurocomputing 459: 395-407 (2021) - [j68]Zhizhen Wan, Huiling Xu, Quanxue Gao:
Multi-view clustering by joint spectral embedding and spectral rotation. Neurocomputing 462: 123-131 (2021) - [j67]De-Yan Xie, Quanxue Gao, Siyang Deng, Xiaojun Yang, Xinbo Gao:
Multiple graphs learning with a new weighted tensor nuclear norm. Neural Networks 133: 57-68 (2021) - [j66]Huiling Xu, Wei Xia, Quanxue Gao, Jungong Han, Xinbo Gao:
Graph embedding clustering: Graph attention auto-encoder with cluster-specificity distribution. Neural Networks 142: 221-230 (2021) - [j65]Quanxue Gao, Pu Zhang, Wei Xia, De-Yan Xie, Xinbo Gao, Dacheng Tao:
Enhanced Tensor RPCA and its Application. IEEE Trans. Pattern Anal. Mach. Intell. 43(6): 2133-2140 (2021) - [j64]Siyang Deng, Wei Xia, Quanxue Gao, Xinbo Gao:
Cross-view classification by joint adversarial learning and class-specificity distribution. Pattern Recognit. 110: 107633 (2021) - [j63]Yang Liu, Xinbo Gao, Quanxue Gao, Jungong Han, Ling Shao:
Relation-based Discriminative Cooperation Network for Zero-Shot Classification. Pattern Recognit. 118: 108024 (2021) - [j62]Xinan Hou, Quanxue Gao, Rong Wang, Xin Luo:
Satellite-Borne Optical Remote Sensing Image Registration Based on Point Features. Sensors 21(8): 2695 (2021) - [j61]Qianqian Wang, Huanhuan Lian, Gan Sun, Quanxue Gao, Licheng Jiao:
iCmSC: Incomplete Cross-Modal Subspace Clustering. IEEE Trans. Image Process. 30: 305-317 (2021) - [j60]Qianqian Wang, Zhengming Ding, Zhiqiang Tao, Quanxue Gao, Yun Fu:
Generative Partial Multi-View Clustering With Adaptive Fusion and Cycle Consistency. IEEE Trans. Image Process. 30: 1771-1783 (2021) - [j59]Qianqian Wang, Quanxue Gao, Linlu Wu, Gan Sun, Licheng Jiao:
Adversarial Multi-Path Residual Network for Image Super-Resolution. IEEE Trans. Image Process. 30: 6648-6658 (2021) - [j58]Qianqian Wang, Jiafeng Cheng, Quanxue Gao, Guoshuai Zhao, Licheng Jiao:
Deep Multi-View Subspace Clustering With Unified and Discriminative Learning. IEEE Trans. Multim. 23: 3483-3493 (2021) - [c23]Qianqian Wang, Wei Xia, Zhiqiang Tao, Quanxue Gao, Xiaochun Cao:
Deep Self-Supervised t-SNE for Multi-modal Subspace Clustering. ACM Multimedia 2021: 1748-1755 - [i4]Tianyu Jiang, Quanxue Gao:
Multiple Graph Learning for Scalable Multi-view Clustering. CoRR abs/2106.15382 (2021) - [i3]Quanxue Gao, Wei Xia, Xinbo Gao, Dacheng Tao:
Effective and Efficient Graph Learning for Multi-view Clustering. CoRR abs/2108.06734 (2021) - [i2]Wei Xia, Quanxue Gao, Ming Yang, Xinbo Gao:
Self-supervised Contrastive Attributed Graph Clustering. CoRR abs/2110.08264 (2021) - 2020
- [j57]De-Yan Xie, Feiping Nie, Quanxue Gao, Song Xiao:
Fast algorithm for large-scale subspace clustering by LRR. IET Image Process. 14(8): 1475-1480 (2020) - [j56]De-Yan Xie, Wei Xia, Qianqian Wang, Quanxue Gao, Song Xiao:
Multi-view clustering by joint manifold learning and tensor nuclear norm. Neurocomputing 380: 105-114 (2020) - [j55]Qianqian Wang, Quanxue Gao, Gan Sun, Chris Ding:
Double robust principal component analysis. Neurocomputing 391: 119-128 (2020) - [j54]Mingzhen Hou, Wei Xia, Xiangdong Zhang, Quanxue Gao:
Discriminative comparison classifier for generalized zero-shot learning. Neurocomputing 414: 10-17 (2020) - [j53]De-Yan Xie, Feiping Nie, Quanxue Gao:
On the optimal solution to maximum margin projection pursuit. Multim. Tools Appl. 79(47): 35441-35461 (2020) - [j52]Yang Liu, Xinbo Gao, Quanxue Gao, Jungong Han, Ling Shao:
Label-activating framework for zero-shot learning. Neural Networks 121: 1-9 (2020) - [j51]De-Yan Xie, Quanxue Gao, Qianqian Wang, Xiangdong Zhang, Xinbo Gao:
Adaptive latent similarity learning for multi-view clustering. Neural Networks 121: 409-418 (2020) - [j50]Quanxue Gao, Zhizhen Wan, Ying Liang, Qianqian Wang, Yang Liu, Ling Shao:
Multi-view projected clustering with graph learning. Neural Networks 126: 335-346 (2020) - [j49]Huiling Xu, Xiangdong Zhang, Wei Xia, Quanxue Gao, Xinbo Gao:
Low-rank tensor constrained co-regularized multi-view spectral clustering. Neural Networks 132: 245-252 (2020) - [j48]De-Yan Xie, Xiangdong Zhang, Quanxue Gao, Jiale Han, Song Xiao, Xinbo Gao:
Multiview Clustering by Joint Latent Representation and Similarity Learning. IEEE Trans. Cybern. 50(11): 4848-4854 (2020) - [c22]Quanxue Gao, Wei Xia, Zhizhen Wan, De-Yan Xie, Pu Zhang:
Tensor-SVD Based Graph Learning for Multi-View Subspace Clustering. AAAI 2020: 3930-3937 - [c21]Quanxue Gao, Huanhuan Lian, Qianqian Wang, Gan Sun:
Cross-Modal Subspace Clustering via Deep Canonical Correlation Analysis. AAAI 2020: 3938-3945 - [c20]Jiafeng Cheng, Qianqian Wang, Zhiqiang Tao, De-Yan Xie, Quanxue Gao:
Multi-View Attribute Graph Convolution Networks for Clustering. IJCAI 2020: 2973-2979 - [i1]Qianqian Wang, Zhengming Ding, Zhiqiang Tao, Quanxue Gao, Yun Fu:
Generative Partial Multi-View Clustering. CoRR abs/2003.13088 (2020)
2010 – 2019
- 2019
- [j47]Qin Li, Yang Liu, Shujian Wang, Quanxue Gao, Xinbo Gao:
Image Classification Using Low-Rank Regularized Extreme Learning Machine. IEEE Access 7: 877-883 (2019) - [j46]De-Yan Xie, Quanxue Gao, Qianqian Wang, Song Xiao:
Multi-View Spectral Clustering via Integrating Global and Local Graphs. IEEE Access 7: 31197-31206 (2019) - [j45]De-Yan Xie, Qin Li, Wei Xia, Shiwei Pang, Huihui He, Quanxue Gao:
Multi-View Classification via Adaptive Discriminant Analysis. IEEE Access 7: 36702-36709 (2019) - [j44]Siyang Deng, Qianqian Wang, Quanxue Gao:
Adaptive Semi-Supervised Classification by Joint Global and Local Graph. IEEE Access 7: 87212-87222 (2019) - [j43]Feng Xiong, Qianqian Wang, Quanxue Gao:
Consistent Embedded GAN for Image-to-Image Translation. IEEE Access 7: 126651-126661 (2019) - [j42]Yang Liu, Caifeng Shan, Quanxue Gao, Xinbo Gao, Jungong Han, Rongmei Cui:
Hyperspectral image denoising via minimizing the partial sum of singular values and superpixel segmentation. Neurocomputing 330: 465-482 (2019) - [j41]Pu Zhang, Siyang Deng, Feiping Nie, Yang Liu, Xiangdong Zhang, Quanxue Gao:
Nuclear-norm based 2DLDA with application to face recognition. Neurocomputing 339: 94-104 (2019) - [j40]Yang Liu, Feiping Nie, Quanxue Gao, Xinbo Gao, Jungong Han, Ling Shao:
Flexible unsupervised feature extraction for image classification. Neural Networks 115: 65-71 (2019) - [j39]Yang Liu, Xinbo Gao, Quanxue Gao, Ling Shao, Jungong Han:
Adaptive robust principal component analysis. Neural Networks 119: 85-92 (2019) - [j38]Quanxue Gao, Sai Xu, Fang Chen, Chris Ding, Xinbo Gao, Yunsong Li:
${R}_1$ -2-DPCA and Face Recognition. IEEE Trans. Cybern. 49(4): 1212-1223 (2019) - [c19]Quanxue Gao, Jiafeng Cheng, De-Yan Xie, Pu Zhang, Wei Xia, Qianqian Wang:
Tensor Linear Regression and Its Application to Color Face Recognition. ICCV Workshops 2019: 523-531 - [c18]Zhaoyang Li, Qianqian Wang, Zhiqiang Tao, Quanxue Gao, Zhaohua Yang:
Deep Adversarial Multi-view Clustering Network. IJCAI 2019: 2952-2958 - [c17]Shuangli Liao, Quanxue Gao, Feiping Nie, Yang Liu, Xiangdong Zhang:
Worst-Case Discriminative Feature Selection. IJCAI 2019: 2973-2979 - [c16]Yang Liu, De-Yan Xie, Quanxue Gao, Jungong Han, Shujian Wang, Xinbo Gao:
Graph and Autoencoder Based Feature Extraction for Zero-shot Learning. IJCAI 2019: 3038-3044 - 2018
- [j37]Yang Liu, Quanxue Gao, Xinbo Gao, Ling Shao:
L2, 1-Norm Discriminant Manifold Learning. IEEE Access 6: 40723-40734 (2018) - [j36]Shujian Wang, De-Yan Xie, Fang Chen, Quanxue Gao:
Dimensionality reduction by LPP-L21. IET Comput. Vis. 12(5): 659-665 (2018) - [j35]Yang Liu, Shuangshuang Zhao, Qianqian Wang, Quanxue Gao:
Learning more distinctive representation by enhanced PCA network. Neurocomputing 275: 924-931 (2018) - [j34]Yang Liu, Feiping Nie, Quanxue Gao:
Nuclear-norm based semi-supervised multiple labels learning. Neurocomputing 275: 940-947 (2018) - [j33]Yue Song, Yang Liu, Quanxue Gao, Xinbo Gao, Feiping Nie, Rongmei Cui:
Euler Label Consistent K-SVD for image classification and action recognition. Neurocomputing 310: 277-286 (2018) - [j32]Yang Liu, Kaiwen Wen, Quanxue Gao, Xinbo Gao, Feiping Nie:
SVM based multi-label learning with missing labels for image annotation. Pattern Recognit. 78: 307-317 (2018) - [j31]Quanxue Gao, Lan Ma, Yang Liu, Xinbo Gao, Feiping Nie:
Angle 2DPCA: A New Formulation for 2DPCA. IEEE Trans. Cybern. 48(5): 1672-1678 (2018) - [j30]Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie:
ℓ2, p -Norm Based PCA for Image Recognition. IEEE Trans. Image Process. 27(3): 1336-1346 (2018) - [j29]Shuangli Liao, Quanxue Gao, Zhaohua Yang, Fang Chen, Feiping Nie, Jungong Han:
Discriminant Analysis via Joint Euler Transform and ℓ2, 1-Norm. IEEE Trans. Image Process. 27(11): 5668-5682 (2018) - [j28]Qianqian Wang, Quanxue Gao, De-Yan Xie, Xinbo Gao, Yong Wang:
Robust DLPP With Nongreedy ℓ1-Norm Minimization and Maximization. IEEE Trans. Neural Networks Learn. Syst. 29(3): 738-743 (2018) - [c15]Shuangli Liao, Jin Li, Yang Liu, Quanxue Gao, Xinbo Gao:
Robust Formulation for PCA: Avoiding Mean Calculation With L2, p-norm Maximization. AAAI 2018: 3604-3610 - [c14]Yang Liu, Quanxue Gao, Jungong Han, Shujian Wang:
Euler Sparse Representation for Image Classification. AAAI 2018: 3691-3697 - [c13]Qianqian Wang, Zhengming Ding, Zhiqiang Tao, Quanxue Gao, Yun Fu:
Partial Multi-view Clustering via Consistent GAN. ICDM 2018: 1290-1295 - [c12]Yang Liu, Quanxue Gao, Zhaohua Yang, Shujian Wang:
Learning with Adaptive Neighbors for Image Clustering. IJCAI 2018: 2483-2489 - [c11]Yang Liu, Quanxue Gao, Jin Li, Jungong Han, Ling Shao:
Zero Shot Learning via Low-rank Embedded Semantic AutoEncoder. IJCAI 2018: 2490-2496 - 2017
- [j27]Mengyuan Li, Jing Wang, Qianqian Wang, Quanxue Gao:
Trace ratio 2DLDA with L1-norm optimization. Neurocomputing 266: 216-225 (2017) - [j26]Tao Li, Mengyuan Li, Quanxue Gao, De-Yan Xie:
F-norm distance metric based robust 2DPCA and face recognition. Neural Networks 94: 204-211 (2017) - [j25]Qianqian Wang, Lan Ma, Quanxue Gao, Yunsong Li, Yunfang Huang, Yang Liu:
Adaptive maximum margin analysis for image recognition. Pattern Recognit. 61: 339-347 (2017) - [j24]Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie:
Optimal mean two-dimensional principal component analysis with F-norm minimization. Pattern Recognit. 68: 286-294 (2017) - [j23]Yang Liu, Quanxue Gao, Shuo Miao, Xinbo Gao, Feiping Nie, Yunsong Li:
A Non-Greedy Algorithm for L1-Norm LDA. IEEE Trans. Image Process. 26(2): 684-695 (2017) - [c10]Qianqian Wang, Quanxue Gao:
Two-Dimensional PCA with F-Norm Minimization. AAAI 2017: 2718-2724 - [c9]Qianqian Wang, Quanxue Gao, Xinbo Gao, Feiping Nie:
Angle Principal Component Analysis. IJCAI 2017: 2936-2942 - 2016
- [j22]Shuo Miao, Jing Wang, Quanxue Gao, Fang Chen, Yong Wang:
Discriminant structure embedding for image recognition. Neurocomputing 174: 850-857 (2016) - [j21]Qianqian Wang, Fang Chen, Quanxue Gao, Xinbo Gao, Feiping Nie:
On the schatten norm for matrix based subspace learning and classification. Neurocomputing 216: 192-199 (2016) - [j20]Quanxue Gao:
Rebuttal to "Comments on 'Joint Global and Local Structure Discriminant Analysis"'. IEEE Trans. Inf. Forensics Secur. 11(2): 429-430 (2016) - [c8]Qianqian Wang, Quanxue Gao:
Robust 2DPCA and Its Application. CVPR Workshops 2016: 1152-1158 - 2015
- [j19]Quanxue Gao, Yunfang Huang, Xinbo Gao, Weiguo Shen, Hailin Zhang:
A novel semi-supervised learning for face recognition. Neurocomputing 152: 69-76 (2015) - [j18]Kai Cui, Quanxue Gao, Hailin Zhang, Xinbo Gao, De-Yan Xie:
Merging model-based two-dimensional principal component analysis. Neurocomputing 168: 1198-1206 (2015) - [j17]Quanxue Gao, Yunfang Huang, Hailin Zhang, Xin Hong, Kui Li, Yong Wang:
Discriminative sparsity preserving projections for image recognition. Pattern Recognit. 48(8): 2543-2553 (2015) - [j16]Quanxue Gao, Qianqian Wang, Yunfang Huang, Xinbo Gao, Xin Hong, Hailin Zhang:
Dimensionality Reduction by Integrating Sparse Representation and Fisher Criterion and its Applications. IEEE Trans. Image Process. 24(12): 5684-5695 (2015) - [c7]Yong Wang, Wenjuan Xu, Xiaoyu Yang, Qianqian Qiao, Zheng Jia, Quanxue Gao:
An Accelerated Two-Step Iteration Hybrid-norm Algorithm for Image Restoration. CCCV (2) 2015: 335-343 - 2014
- [j15]Qianqian Wang, Xiaolei Hu, Quanxue Gao, Bing Li, Yong Wang:
Global-local fisher discriminant approach for face recognition. Neural Comput. Appl. 25(5): 1137-1144 (2014) - [j14]Quanxue Gao, Jingjing Liu, Kai Cui, Hailin Zhang, Xiaogang Wang:
Stable locality sensitive discriminant analysis for image recognition. Neural Networks 54: 49-56 (2014) - 2013
- [j13]Quanxue Gao, Xiujuan Hao, Qijun Zhao, Weiguo Shen, Jingjie Ma:
Feature extraction using two-dimensional neighborhood margin and variation embedding. Comput. Vis. Image Underst. 117(5): 525-531 (2013) - [j12]Quanxue Gao, Haijun Zhang, Xiaojing Yang, Jingjing Liu, Yamin Liu:
Joint geometry and variability for image recognition. Neurocomputing 99: 241-249 (2013) - [j11]Quanxue Gao, Jingjing Liu, Hailin Zhang, Xinbo Gao, Kui Li:
Joint Global and Local Structure Discriminant Analysis. IEEE Trans. Inf. Forensics Secur. 8(4): 626-635 (2013) - [j10]Quanxue Gao, Jingjie Ma, Hailin Zhang, Xinbo Gao, Yamin Liu:
Stable Orthogonal Local Discriminant Embedding for Linear Dimensionality Reduction. IEEE Trans. Image Process. 22(7): 2521-2531 (2013) - [j9]Quanxue Gao, Feifei Gao, Hailin Zhang, Xiujuan Hao, Xiaogang Wang:
Two-Dimensional Maximum Local Variation Based on Image Euclidean Distance for Face Recognition. IEEE Trans. Image Process. 22(10): 3807-3817 (2013) - 2012
- [j8]Quanxue Gao, Haijun Zhang, Jingjing Liu:
Two-dimensional margin, similarity and variation embedding. Neurocomputing 86: 179-183 (2012) - [j7]Quanxue Gao, Jingjing Liu, Haijun Zhang, Jun Hou, Xiaojing Yang:
Enhanced fisher discriminant criterion for image recognition. Pattern Recognit. 45(10): 3717-3724 (2012) - 2010
- [j6]Quanxue Gao, Hui Xu, Yiying Li, De-Yan Xie:
Two-dimensional supervised local similarity and diversity projection. Pattern Recognit. 43(10): 3359-3363 (2010) - [j5]Quanxue Gao, Lei Zhang, David Zhang, Hui Xu:
Independent components extraction from image matrix. Pattern Recognit. Lett. 31(3): 171-178 (2010) - [c6]Yiying Li, Qichuan Tian, Quanxue Gao, Jing Xu:
Directional Two-dimensional Neighborhood Preserving Projection for Face Recognition. CASoN 2010: 357-360 - [c5]Quanxue Gao, Jun Hou, Xiujuan Hao, Yiying Li:
Directional Multimode Subspace Analysis with Tensor Representation-Discriminant Feature Extraction. CASoN 2010: 361-364 - [c4]Quanxue Gao, Yiying Li, Yamin Liu, Haijun Zhang:
Directional Principal Component Analysis for Image Matrix. CASoN 2010: 374-377
2000 – 2009
- 2009
- [j4]Quanxue Gao, Lei Zhang, David Zhang:
Sequential row-column independent component analysis for face recognition. Neurocomputing 72(4-6): 1152-1159 (2009) - 2008
- [j3]Quanxue Gao, Lei Zhang, David Zhang:
Face recognition using FLDA with single training image per person. Appl. Math. Comput. 205(2): 726-734 (2008) - [c3]Lei Zhang, Quanxue Gao, David Zhang:
Directional independent component analysis with tensor representation. CVPR 2008 - [c2]Qin Li, Xue-Min Jin, Quanxue Gao, Jane You, Prabir Bhattacharya:
Screening Diabetic Retinopathy Through Color Retinal Images. ICMB 2008: 176-183 - 2007
- [j2]Quanxue Gao:
Is two-dimensional PCA equivalent to a special case of modular PCA? Pattern Recognit. Lett. 28(10): 1250-1251 (2007) - [j1]Quanxue Gao, Lei Zhang, David Zhang, Jian Yang:
Comments on "On Image Matrix Based Feature Extraction Algorithms". IEEE Trans. Syst. Man Cybern. Part B 37(5): 1373-1374 (2007) - [c1]Lei Zhang, Quanxue Gao, David Zhang:
Block Independent Component Analysis for Face Recognition. ICIAP 2007: 217-222
Coauthor Index
[j107] [j106] [j105] [j104] [j103] [j102] [j98] [j97] [j96] [j94] [j93] [j92] [j91] [j90] [i6] [i5] [j84] [j79] [j78] [j77] [j75] [j74] [j73] [j72] [j71] [j70] [j67] [j66] [j65] [j64] [j63] [i3] [i2] [j52] [j51] [j49] [j48] [j47] [j42] [j40] [j39] [j38] [c16] [j37] [j33] [j32] [j31] [j30] [j28] [c15] [j24] [j23] [c9] [j21] [j19] [j18] [j16] [j11] [j10]
[j115] [j113] [j108] [j106] [j105] [j104] [j103] [j102] [j101] [c37] [c36] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [i12] [i10] [i9] [j94] [j93] [j90] [j89] [c27] [c26] [c25] [c24] [i6] [i5] [j85] [j81] [j78] [j75] [j71] [j61] [j60] [j59] [j58] [c23] [j56] [j55] [j51] [j50] [c21] [c20] [i1] [j46] [j44] [j43] [c19] [c18] [j35] [j30] [j28] [c13] [j27] [j25] [j24] [c10] [c9] [j21] [c8] [j16] [j15]
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