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ORCIDZhao Kang 0001
Person information
- affiliation: University of Electronic Science and Technology of China, School of Computer Science and Engineering, Chengdu, China
- affiliation (PhD 2017): Southern Illinois University Carbondale, IL, US
Other persons with the same name
- Zhao Kang 0002 — Wuhan University, Mapping and Remote Sensing, China
- Zhao Kang 0003 — Army Engineering University of PLA, Field Engineering College, Nanjing, China
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2020 – today
- 2024
[j59]Fatemeh Sadjadi, Mina Jamshidi
, Zhao Kang:
Multi-view subspace clustering using drop out technique on points. Int. J. Mach. Learn. Cybern. 15(5): 1841-1854 (2024)- [j58]Chao Huang, Zhao Kang, Hong Wu:
A Prototype-Based Neural Network for Image Anomaly Detection and Localization. Neural Process. Lett. 56(3): 169 (2024) - [j57]Chong Peng, Kehan Kang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Fine-Grained Essential Tensor Learning for Robust Multi-View Spectral Clustering. IEEE Trans. Image Process. 33: 3145-3160 (2024) - [j56]Jiangzhang Gan, Rongyao Hu, Yujie Mo, Zhao Kang, Liang Peng, Yonghua Zhu, Xiaofeng Zhu:
Multigraph Fusion for Dynamic Graph Convolutional Network. IEEE Trans. Neural Networks Learn. Syst. 35(1): 196-207 (2024) - [c44]Bingheng Li, Erlin Pan, Zhao Kang:
PC-Conv: Unifying Homophily and Heterophily with Two-Fold Filtering. AAAI 2024: 13437-13445 - [c43]Xiaowei Qian, Bingheng Li, Zhao Kang:
Upper Bounding Barlow Twins: A Novel Filter for Multi-Relational Clustering. AAAI 2024: 14660-14668 - [c42]Xudong Zhu, Zhao Kang, Bei Hui:
FCDS: Fusing Constituency and Dependency Syntax into Document-Level Relation Extraction. LREC/COLING 2024: 7141-7152 - [c41]Chong Peng, Pengfei Zhang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Shawn Cheng:
Fine-Grained Bipartite Concept Factorization for Clustering. CVPR 2024: 26254-26264 - [c40]Yu Zhang, Kehai Chen, Xuefeng Bai, Zhao Kang, Quanjiang Guo, Min Zhang:
Question-guided Knowledge Graph Re-scoring and Injection for Knowledge Graph Question Answering. EMNLP (Findings) 2024: 8972-8985 - [c39]Yuhang Cheng, Kaiwen Li, Zhao Kang:
EMKG: Efficient Matchings for Knowledge Graph Integration in Stance Detection. IJCNN 2024: 1-8 - [c38]Yu Zhang, Zhao Kang:
TPN: Transferable Proto-Learning Network towards Few-shot Document-Level Relation Extraction. IJCNN 2024: 1-9 - [c37]Zhixiang Shen, Haolan He, Zhao Kang:
Balanced Multi-Relational Graph Clustering. ACM Multimedia 2024: 4120-4128 - [i62]Xudong Zhu, Zhao Kang, Bei Hui:
FCDS: Fusing Constituency and Dependency Syntax into Document-Level Relation Extraction. CoRR abs/2403.01886 (2024) - [i61]Xuanting Xie, Zhao Kang, Wenyu Chen:
Robust Graph Structure Learning under Heterophily. CoRR abs/2403.03659 (2024) - [i60]Xuanting Xie, Erlin Pan, Zhao Kang, Wenyu Chen, Bingheng Li:
Provable Filter for Real-world Graph Clustering. CoRR abs/2403.03666 (2024) - [i59]Zhao Kang, Xuanting Xie, Bingheng Li, Erlin Pan:
CDC: A Simple Framework for Complex Data Clustering. CoRR abs/2403.03670 (2024) - [i58]Bingheng Li, Xuanting Xie, Haoxiang Lei, Ruiyi Fang, Zhao Kang:
Simplified PCNet with Robustness. CoRR abs/2403.03676 (2024) - [i57]Zhixiang Shen, Haolan He, Zhao Kang:
Balanced Multi-Relational Graph Clustering. CoRR abs/2407.16863 (2024) - [i56]Zhixiang Shen, Zhao Kang:
When Heterophily Meets Heterogeneous Graphs: Latent Graphs Guided Unsupervised Representation Learning. CoRR abs/2409.00687 (2024) - [i55]Zhixiang Shen, Shuo Wang, Zhao Kang:
Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning. CoRR abs/2409.17386 (2024) - [i54]Yu Zhang, Zhao Kang:
TPN: Transferable Proto-Learning Network towards Few-shot Document-Level Relation Extraction. CoRR abs/2410.00412 (2024) - [i53]Yu Zhang, Kehai Chen, Xuefeng Bai, Zhao Kang, Quanjiang Guo, Min Zhang:
Question-guided Knowledge Graph Re-scoring and Injection for Knowledge Graph Question Answering. CoRR abs/2410.01401 (2024) - 2023
- [j55]Xuanting Xie, Wenyu Chen, Zhao Kang, Chong Peng:
Contrastive graph clustering with adaptive filter. Expert Syst. Appl. 219: 119645 (2023) - [j54]Erlin Pan, Zhao Kang:
High-order multi-view clustering for generic data. Inf. Fusion 100: 101947 (2023) - [j53]Wang-Tao Zhou, Zhao Kang, Ling Tian, Yi Su:
Intensity-free convolutional temporal point process: Incorporating local and global event contexts. Inf. Sci. 646: 119318 (2023) - [j52]Jiaqi Li, Haojia Kong, Gezheng Xu, Changjian Shui, Ruizhi Pu, Zhao Kang, Charles X. Ling, Boyu Wang:
Label shift conditioned hybrid querying for deep active learning. Knowl. Based Syst. 274: 110616 (2023) - [j51]Chong Peng, Xingrong Hou, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Global and local similarity learning in multi-kernel space for nonnegative matrix factorization. Knowl. Based Syst. 279: 110946 (2023) - [j50]Liang Liu, Ling Tian, Zhao Kang, Tianqi Wan:
Spacecraft anomaly detection with attention temporal convolution networks. Neural Comput. Appl. 35(13): 9753-9761 (2023) - [j49]Zhao Kang, Hongfei Liu, Jiangxin Li, Xiaofeng Zhu, Ling Tian:
Self-paced principal component analysis. Pattern Recognit. 142: 109692 (2023) - [j48]Zhiping Lin, Zhao Kang, Lizong Zhang, Ling Tian:
Multi-View Attributed Graph Clustering. IEEE Trans. Knowl. Data Eng. 35(2): 1872-1880 (2023) - [j47]Lingling Zhang, Zhiwei Zhang, Guoren Wang, Ye Yuan, Zhao Kang:
Efficiently Counting Triangles for Hypergraph Streams by Reservoir-Based Sampling. IEEE Trans. Knowl. Data Eng. 35(11): 11328-11341 (2023) - [c36]Erlin Pan, Zhao Kang:
Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering. ICML 2023: 26868-26877 - [c35]Qian Zhang, Zhao Kang, Zenglin Xu, Hongguang Fu:
Contrastive Kernel Subspace Clustering. ICONIP (5) 2023: 399-410 - [c34]Quanjiang Guo, Zhao Kang, Ling Tian, Zhouguo Chen:
TieFake: Title-Text Similarity and Emotion-Aware Fake News Detection. IJCNN 2023: 1-7 - [c33]Ziqian Yan, Zhao Kang, Ling Tian:
Self-Attention-Based Reconstruction for Planetary Magnetic Field. NCAA (1) 2023: 147-159 - [c32]Hongfei Liu, Zhao Kang, Lizong Zhang, Ling Tian, Fujun Hua:
Document-Level Relation Extraction with Cross-sentence Reasoning Graph. PAKDD (1) 2023: 316-328 - [i52]Hongfei Liu, Zhao Kang, Lizong Zhang, Ling Tian, Fujun Hua:
Document-level Relation Extraction with Cross-sentence Reasoning Graph. CoRR abs/2303.03912 (2023) - [i51]Liang Liu, Ling Tian, Zhao Kang, Tianqi Wan:
Spacecraft Anomaly Detection with Attention Temporal Convolution Network. CoRR abs/2303.06879 (2023) - [i50]Quanjiang Guo, Zhao Kang, Ling Tian, Zhouguo Chen:
TieFake: Title-Text Similarity and Emotion-Aware Fake News Detection. CoRR abs/2304.09421 (2023) - [i49]Erlin Pan, Zhao Kang:
Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering. CoRR abs/2305.02931 (2023) - [i48]Wang-Tao Zhou, Zhao Kang, Ling Tian, Yi Su:
Intensity-free Convolutional Temporal Point Process: Incorporating Local and Global Event Contexts. CoRR abs/2306.14072 (2023) - [i47]Chao Huang, Zhao Kang, Hong Wu:
A Prototype-Based Neural Network for Image Anomaly Detection and Localization. CoRR abs/2310.02576 (2023) - [i46]Wang-Tao Zhou, Zhao Kang, Ling Tian:
Non-Autoregressive Diffusion-based Temporal Point Processes for Continuous-Time Long-Term Event Prediction. CoRR abs/2311.01033 (2023) - [i45]Xiaowei Qian, Bingheng Li, Zhao Kang:
Upper Bounding Barlow Twins: A Novel Filter for Multi-Relational Clustering. CoRR abs/2312.14066 (2023) - [i44]Bingheng Li, Erlin Pan, Zhao Kang:
PC-Conv: Unifying Homophily and Heterophily with Two-fold Filtering. CoRR abs/2312.14438 (2023) - 2022
- [j46]Chong Peng, Zhilu Zhang, Chenglizhao Chen, Zhao Kang, Qiang Cheng:
Two-dimensional semi-nonnegative matrix factorization for clustering. Inf. Sci. 590: 106-141 (2022) - [j45]Liang Liu, Zhao Kang, Jiajia Ruan, Xixu He:
Multilayer graph contrastive clustering network. Inf. Sci. 613: 256-267 (2022) - [j44]Yong Dai, Linjun Shou, Ming Gong, Xiaolin Xia, Zhao Kang, Zenglin Xu, Daxin Jiang:
Graph Fusion Network for Text Classification. Knowl. Based Syst. 236: 107659 (2022) - [j43]Chong Peng, Yiqun Zhang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Log-based sparse nonnegative matrix factorization for data representation. Knowl. Based Syst. 251: 109127 (2022) - [j42]Qian Zhang, Zhao Kang, Zenglin Xu, Shudong Huang, Hongguang Fu:
Spaks: Self-paced multiple kernel subspace clustering with feature smoothing regularization. Knowl. Based Syst. 253: 109500 (2022) - [j41]Chong Peng, Jing Zhang, Yongyong Chen, Xin Xing, Chenglizhao Chen, Zhao Kang, Li Guo, Qiang Cheng:
Preserving bilateral view structural information for subspace clustering. Knowl. Based Syst. 258: 109915 (2022) - [j40]Li Ren, Guiduo Duan, Tianxi Huang, Zhao Kang:
Multi-local feature relation network for few-shot learning. Neural Comput. Appl. 34(10): 7393-7403 (2022) - [j39]Liang Liu, Peng Chen, Guangchun Luo, Zhao Kang, Yonggang Luo, Sanchu Han:
Scalable multi-view clustering with graph filtering. Neural Comput. Appl. 34(19): 16213-16221 (2022) - [j38]Zhao Kang, Zhiping Lin, Xiaofeng Zhu, Wenbo Xu:
Structured Graph Learning for Scalable Subspace Clustering: From Single View to Multiview. IEEE Trans. Cybern. 52(9): 8976-8986 (2022) - [j37]Chong Peng, Yang Liu, Kehan Kang, Yongyong Chen, Xinxing Wu, Andrew Cheng, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Hyperspectral Image Denoising Using Nonconvex Local Low-Rank and Sparse Separation With Spatial-Spectral Total Variation Regularization. IEEE Trans. Geosci. Remote. Sens. 60: 1-17 (2022) - [c31]Zekun Li, Zhengyang Geng, Zhao Kang, Wenyu Chen, Yibo Yang:
Eliminating Gradient Conflict in Reference-based Line-Art Colorization. ECCV (17) 2022: 579-596 - [c30]Ruiyi Fang, Liangjian Wen, Zhao Kang, Jianzhuang Liu:
Structure-Preserving Graph Representation Learning. ICDM 2022: 927-932 - [c29]Zhao Kang, Zhanyu Liu, Shirui Pan, Ling Tian:
Fine-grained Attributed Graph Clustering. SDM 2022: 370-378 - [i43]Chong Peng, Yang Liu, Yongyong Chen, Xinxin Wu, Andrew Cheng, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Hyperspectral Image Denoising Using Non-convex Local Low-rank and Sparse Separation with Spatial-Spectral Total Variation Regularization. CoRR abs/2201.02812 (2022) - [i42]Chong Peng, Yiqun Zhang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Log-based Sparse Nonnegative Matrix Factorization for Data Representation. CoRR abs/2204.10647 (2022) - [i41]Liang Liu, Peng Chen, Guangchun Luo, Zhao Kang, Yonggang Luo, Sanchu Han:
Scalable Multi-view Clustering with Graph Filtering. CoRR abs/2205.09228 (2022) - [i40]Zekun Li, Zhengyang Geng, Zhao Kang, Wenyu Chen, Yibo Yang:
Eliminating Gradient Conflict in Reference-based Line-Art Colorization. CoRR abs/2207.06095 (2022) - [i39]Ruiyi Fang, Liangjian Wen, Zhao Kang, Jianzhuang Liu:
Structure-Preserving Graph Representation Learning. CoRR abs/2209.00793 (2022) - [i38]Erlin Pan, Zhao Kang:
High-order Multi-view Clustering for Generic Data. CoRR abs/2209.10838 (2022) - 2021
- [j36]Peng Zhao, Wenhua Zang, Bin Liu, Zhao Kang, Kun Bai, Kaizhu Huang, Zenglin Xu:
Domain adaptation with feature and label adversarial networks. Neurocomputing 439: 294-301 (2021) - [j35]Juncheng Lv, Zhao Kang, Boyu Wang, Luping Ji, Zenglin Xu:
Multi-view subspace clustering via partition fusion. Inf. Sci. 560: 410-423 (2021) - [j34]Chong Peng, Zhilu Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Nonnegative matrix factorization with local similarity learning. Inf. Sci. 562: 325-346 (2021) - [j33]Chong Peng, Yang Liu, Xin Zhang, Zhao Kang, Yongyong Chen, Chenglizhao Chen, Qiang Cheng:
Learning discriminative representation for image classification. Knowl. Based Syst. 233: 107517 (2021) - [j32]Zhao Kang, Chong Peng, Qiang Cheng, Xinwang Liu, Xi Peng, Zenglin Xu, Ling Tian:
Structured graph learning for clustering and semi-supervised classification. Pattern Recognit. 110: 107627 (2021) - [j31]Chong Peng, Qian Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Kernel two-dimensional ridge regression for subspace clustering. Pattern Recognit. 113: 107749 (2021) - [j30]Shudong Huang, Zhao Kang, Zenglin Xu, Quanhui Liu:
Robust deep k-means: An effective and simple method for data clustering. Pattern Recognit. 117: 107996 (2021) - [j29]Hongyuan Zhu, Yi Cheng, Xi Peng, Joey Tianyi Zhou, Zhao Kang, Shijian Lu, Zhiwen Fang, Liyuan Li, Joo-Hwee Lim:
Single-Image Dehazing via Compositional Adversarial Network. IEEE Trans. Cybern. 51(2): 829-838 (2021) - [j28]Boyu Wang, Chi Man Wong, Zhao Kang, Feng Liu, Changjian Shui, Feng Wan, C. L. Philip Chen:
Common Spatial Pattern Reformulated for Regularizations in Brain-Computer Interfaces. IEEE Trans. Cybern. 51(10): 5008-5020 (2021) - [j27]Juncheng Lv, Zhao Kang, Xiao Lu, Zenglin Xu:
Pseudo-Supervised Deep Subspace Clustering. IEEE Trans. Image Process. 30: 5252-5263 (2021) - [c28]Jiangxin Li, Zhao Kang, Chong Peng, Wenyu Chen:
Self-Paced Two-dimensional PCA. AAAI 2021: 8392-8400 - [c27]Zhiping Lin, Zhao Kang:
Graph Filter-based Multi-view Attributed Graph Clustering. IJCAI 2021: 2723-2729 - [c26]Changshu Liu, Liangjian Wen, Zhao Kang, Guangchun Luo, Ling Tian:
Self-supervised Consensus Representation Learning for Attributed Graph. ACM Multimedia 2021: 2654-2662 - [c25]Peng Chen, Liang Liu, Zhengrui Ma, Zhao Kang:
Smoothed Multi-view Subspace Clustering. NCAA 2021: 128-140 - [c24]Erlin Pan, Zhao Kang:
Multi-view Contrastive Graph Clustering. NeurIPS 2021: 2148-2159 - [i37]Zhao Kang, Zhiping Lin, Xiaofeng Zhu, Wenbo Xu:
Structured Graph Learning for Scalable Subspace Clustering: From Single-view to Multi-view. CoRR abs/2102.07943 (2021) - [i36]Juncheng Lv, Zhao Kang, Xiao Lu, Zenglin Xu:
Pseudo-supervised Deep Subspace Clustering. CoRR abs/2104.03531 (2021) - [i35]Zhengrui Ma, Zhao Kang, Guangchun Luo, Ling Tian:
Towards Clustering-friendly Representations: Subspace Clustering via Graph Filtering. CoRR abs/2106.09874 (2021) - [i34]Peng Chen, Liang Liu, Zhengrui Ma, Zhao Kang:
Smoothed Multi-View Subspace Clustering. CoRR abs/2106.09875 (2021) - [i33]Zhao Kang, Hongfei Liu, Jiangxin Li, Xiaofeng Zhu, Ling Tian:
Self-paced Principal Component Analysis. CoRR abs/2106.13880 (2021) - [i32]Changshu Liu, Liangjian Wen, Zhao Kang, Guangchun Luo, Ling Tian:
Self-supervised Consensus Representation Learning for Attributed Graph. CoRR abs/2108.04822 (2021) - [i31]Erlin Pan, Zhao Kang:
Multi-view Contrastive Graph Clustering. CoRR abs/2110.11842 (2021) - [i30]Liang Liu, Zhao Kang, Ling Tian, Wenbo Xu, Xixu He:
Multilayer Graph Contrastive Clustering Network. CoRR abs/2112.14021 (2021) - 2020
- [j26]Shudong Huang, Zenglin Xu, Zhao Kang, Yazhou Ren:
Regularized nonnegative matrix factorization with adaptive local structure learning. Neurocomputing 382: 196-209 (2020) - [j25]Dan Ma, Bin Liu, Zhao Kang, Jiayu Zhou, Jianke Zhu, Zenglin Xu:
Two birds with one stone: Transforming and generating facial images with iterative GAN. Neurocomputing 396: 278-290 (2020) - [j24]Shudong Huang, Zenglin Xu, Ivor W. Tsang, Zhao Kang:
Auto-weighted multi-view co-clustering with bipartite graphs. Inf. Sci. 512: 18-30 (2020) - [j23]Chong Peng, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Robust principal component analysis: A factorization-based approach with linear complexity. Inf. Sci. 513: 581-599 (2020) - [j22]Zhao Kang, Guoxin Shi, Shudong Huang, Wenyu Chen, Xiaorong Pu, Joey Tianyi Zhou, Zenglin Xu:
Multi-graph fusion for multi-view spectral clustering. Knowl. Based Syst. 189 (2020) - [j21]Zhao Kang, Xinjia Zhao, Chong Peng, Hongyuan Zhu, Joey Tianyi Zhou, Xi Peng, Wenyu Chen, Zenglin Xu:
Partition level multiview subspace clustering. Neural Networks 122: 279-288 (2020) - [j20]Zhao Kang, Xiao Lu, Yiwei Lu, Chong Peng, Wenyu Chen, Zenglin Xu:
Structure learning with similarity preserving. Neural Networks 129: 138-148 (2020) - [j19]Zhao Kang, Xiao Lu, Jian Liang, Kun Bai, Zenglin Xu:
Relation-Guided Representation Learning. Neural Networks 131: 93-102 (2020) - [j18]Shudong Huang, Zhao Kang, Zenglin Xu:
Auto-weighted multi-view clustering via deep matrix decomposition. Pattern Recognit. 97 (2020) - [j17]Juan Chen, Shijie Zhou, Zhao Kang, Quan Wen:
Locality-constrained group lasso coding for microvessel image classification. Pattern Recognit. Lett. 130: 132-138 (2020) - [j16]Zhao Kang, Haiqi Pan, Steven C. H. Hoi, Zenglin Xu:
Robust Graph Learning From Noisy Data. IEEE Trans. Cybern. 50(5): 1833-1843 (2020) - [j15]Zheng Wang, Lin Zuo, Jing Ma, Si Chen, Jingjing Li, Zhao Kang, Lei Zhang:
Exploring nonnegative and low-rank correlation for noise-resistant spectral clustering. World Wide Web 23(3): 2107-2127 (2020) - [c23]Zhao Kang, Wangtao Zhou, Zhitong Zhao, Junming Shao, Meng Han, Zenglin Xu:
Large-Scale Multi-View Subspace Clustering in Linear Time. AAAI 2020: 4412-4419 - [c22]Changsheng Li, Handong Ma, Zhao Kang, Ye Yuan, Xiaoyu Zhang, Guoren Wang:
On Deep Unsupervised Active Learning. IJCAI 2020: 2626-2632 - [c21]Zhengrui Ma, Zhao Kang, Guangchun Luo, Ling Tian, Wenyu Chen:
Towards Clustering-friendly Representations: Subspace Clustering via Graph Filtering. ACM Multimedia 2020: 3081-3089 - [c20]Xiao Lu, Zhao Kang, Jiachun Tang, Shuang Xie, Yuanzhang Su:
Generalized Locally-Linear Embedding: A Neural Network Implementation. NCAA 2020: 97-106 - [c19]Shudong Huang, Zhao Kang, Zenglin Xu:
Deep K-Means: A Simple and Effective Method for Data Clustering. NCAA 2020: 272-283 - [i29]Chong Peng, Zhilu Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Two-Dimensional Semi-Nonnegative Matrix Factorization for Clustering. CoRR abs/2005.09229 (2020) - [i28]Zhao Kang, Xiao Lu, Jian Liang, Kun Bai, Zenglin Xu:
Relation-Guided Representation Learning. CoRR abs/2007.05742 (2020) - [i27]Changsheng Li, Handong Ma, Zhao Kang, Ye Yuan, Xiaoyu Zhang, Guoren Wang:
On Deep Unsupervised Active Learning. CoRR abs/2007.13959 (2020) - [i26]Zhao Kang, Chong Peng, Qiang Cheng, Xinwang Liu, Xi Peng, Zenglin Xu, Ling Tian:
Structured Graph Learning for Clustering and Semi-supervised Classification. CoRR abs/2008.13429 (2020) - [i25]Chong Peng, Qian Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Kernel Two-Dimensional Ridge Regression for Subspace Clustering. CoRR abs/2011.01477 (2020)
2010 – 2019
- 2019
- [j14]Zhao Kang, Honghui Xu, Boyu Wang, Hongyuan Zhu, Zenglin Xu:
Clustering with similarity preserving. Neurocomputing 365: 211-218 (2019) - [j13]Zhao Kang, Liangjian Wen, Wenyu Chen, Zenglin Xu:
Low-rank kernel learning for graph-based clustering. Knowl. Based Syst. 163: 510-517 (2019) - [j12]Shudong Huang, Zhao Kang, Ivor W. Tsang, Zenglin Xu:
Auto-weighted multi-view clustering via kernelized graph learning. Pattern Recognit. 88: 174-184 (2019) - [c18]Zhao Kang, Yiwei Lu, Yuanzhang Su, Changsheng Li, Zenglin Xu:
Similarity Learning via Kernel Preserving Embedding. AAAI 2019: 4057-4064 - [c17]Xiaofan Bo, Zhao Kang, Zhitong Zhao, Yuanzhang Su, Wenyu Chen:
Latent Multi-view Semi-Supervised Classification. ACML 2019: 348-362 - [c16]Chong Peng, Chenglizhao Chen, Zhao Kang, Jianbo Li, Qiang Cheng:
RES-PCA: A Scalable Approach to Recovering Low-Rank Matrices. CVPR 2019: 7317-7325 - [c15]Zhao Kang, Zipeng Guo, Shudong Huang, Siying Wang, Wenyu Chen, Yuanzhang Su, Zenglin Xu:
Multiple Partitions Aligned Clustering. IJCAI 2019: 2701-2707 - [i24]Zhao Kang, Yiwei Lu, Yuanzhang Su, Changsheng Li, Zenglin Xu:
Similarity Learning via Kernel Preserving Embedding. CoRR abs/1903.04235 (2019) - [i23]Zhao Kang, Liangjian Wen, Wenyu Chen, Zenglin Xu:
Low-rank Kernel Learning for Graph-based Clustering. CoRR abs/1903.05962 (2019) - [i22]Chong Peng, Chenglizhao Chen, Zhao Kang, Jianbo Li, Qiang Cheng:
RES-PCA: A Scalable Approach to Recovering Low-rank Matrices. CoRR abs/1904.07497 (2019) - [i21]Zhao Kang, Honghui Xu, Boyu Wang, Hongyuan Zhu, Zenglin Xu:
Clustering with Similarity Preserving. CoRR abs/1905.08419 (2019) - [i20]Chong Peng, Zhao Kang, Chenglizhao Chen, Qiang Cheng:
Nonnegative Matrix Factorization with Local Similarity Learning. CoRR abs/1907.04150 (2019) - [i19]Xiaofan Bo, Zhao Kang, Zhitong Zhao, Yuanzhang Su, Wenyu Chen:
Latent Multi-view Semi-Supervised Classification. CoRR abs/1909.03712 (2019) - [i18]Zhao Kang, Zipeng Guo, Shudong Huang, Siying Wang, Wenyu Chen, Yuanzhang Su, Zenglin Xu:
Multiple Partitions Aligned Clustering. CoRR abs/1909.06008 (2019) - [i17]Zhao Kang, Guoxin Shi, Shudong Huang, Wenyu Chen, Xiaorong Pu, Joey Tianyi Zhou, Zenglin Xu:
Multi-graph Fusion for Multi-view Spectral Clustering. CoRR abs/1909.06940 (2019) - [i16]Zhao Kang, Wangtao Zhou, Zhitong Zhao, Junming Shao, Meng Han, Zenglin Xu:
Large-scale Multi-view Subspace Clustering in Linear Time. CoRR abs/1911.09290 (2019) - [i15]Zhao Kang, Xiao Lu, Yiwei Lu, Chong Peng, Zenglin Xu:
Structure Learning with Similarity Preserving. CoRR abs/1912.01197 (2019) - [i14]Juncheng Lv, Zhao Kang, Boyu Wang, Luping Ji, Zenglin Xu:
Multi-view Subspace Clustering via Partition Fusion. CoRR abs/1912.01201 (2019) - 2018
- [j11]Shudong Huang, Zhao Kang, Zenglin Xu:
Self-weighted multi-view clustering with soft capped norm. Knowl. Based Syst. 158: 1-8 (2018) - [j10]Shuting Cai, Zhao Kang, Ming Yang, Xiaoming Xiong, Chong Peng, Mingqing Xiao:
Image Denoising via Improved Dictionary Learning with Global Structure and Local Similarity Preservations. Symmetry 10(5): 167 (2018) - [j9]Chong Peng, Zhao Kang, Shuting Cai, Qiang Cheng:
Integrate and Conquer: Double-Sided Two-Dimensional k-Means Via Integrating of Projection and Manifold Construction. ACM Trans. Intell. Syst. Technol. 9(5): 57:1-57:25 (2018) - [c14]Zhao Kang, Chong Peng, Qiang Cheng, Zenglin Xu:
Unified Spectral Clustering With Optimal Graph. AAAI 2018: 3366-3373 - [c13]Zhao Kang, Xiao Lu, Jinfeng Yi, Zenglin Xu:
Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification. IJCAI 2018: 2312-2318 - [i13]Zhao Kang, Xiao Lu, Jinfeng Yi, Zenglin Xu:
Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification. CoRR abs/1806.07697 (2018) - [i12]Zhao Kang, Haiqi Pan, Steven C. H. Hoi, Zenglin Xu:
Robust Graph Learning from Noisy Data. CoRR abs/1812.06673 (2018) - 2017
- [j8]Chong Peng, Zhao Kang, Qiang Cheng:
Integrating feature and graph learning with low-rank representation. Neurocomputing 249: 106-116 (2017) - [j7]Zhao Kang, Chong Peng, Qiang Cheng:
Kernel-driven similarity learning. Neurocomputing 267: 210-219 (2017) - [j6]Chong Peng, Zhao Kang, Fei Xu, Yongyong Chen, Qiang Cheng:
Image Projection Ridge Regression for Subspace Clustering. IEEE Signal Process. Lett. 24(7): 991-995 (2017) - [j5]Chong Peng, Zhao Kang, Yunhong Hu, Jie Cheng, Qiang Cheng:
Nonnegative Matrix Factorization with Integrated Graph and Feature Learning. ACM Trans. Intell. Syst. Technol. 8(3): 42:1-42:29 (2017) - [j4]Chong Peng, Zhao Kang, Yunhong Hu, Jie Cheng, Qiang Cheng:
Robust Graph Regularized Nonnegative Matrix Factorization for Clustering. ACM Trans. Knowl. Discov. Data 11(3): 33:1-33:30 (2017) - [c12]Zhao Kang, Chong Peng, Qiang Cheng:
Twin Learning for Similarity and Clustering: A Unified Kernel Approach. AAAI 2017: 2080-2086 - [c11]Chong Peng, Zhao Kang, Qiang Cheng:
Subspace Clustering via Variance Regularized Ridge Regression. CVPR 2017: 682-691 - [c10]Zhao Kang, Chong Peng, Ming Yang, Qiang Cheng:
Exploiting Nonlinear Relationships for Top-N Recommender Systems. ICBK 2017: 49-56 - [c9]Zhao Kang, Chong Peng, Qiang Cheng:
Clustering with Adaptive Manifold Structure Learning. ICDE 2017: 79-82 - [i11]Zhao Kang, Chong Peng, Qiang Cheng:
Twin Learning for Similarity and Clustering: A Unified Kernel Approach. CoRR abs/1705.00678 (2017) - [i10]Zhao Kang, Chong Peng, Qiang Cheng, Zenglin Xu:
Unified Spectral Clustering with Optimal Graph. CoRR abs/1711.04258 (2017) - [i9]Dan Ma, Bin Liu, Zhao Kang, Jianke Zhu, Zenglin Xu:
Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs. CoRR abs/1711.06078 (2017) - 2016
- [j3]Chong Peng, Zhao Kang, Ming Yang, Qiang Cheng:
Feature Selection Embedded Subspace Clustering. IEEE Signal Process. Lett. 23(7): 1018-1022 (2016) - [c8]Zhao Kang, Chong Peng, Qiang Cheng:
Top-N Recommender System via Matrix Completion. AAAI 2016: 179-185 - [c7]Zhao Kang, Chong Peng, Ming Yang, Qiang Cheng:
Top-N Recommendation on Graphs. CIKM 2016: 2101-2106 - [c6]Chong Peng, Zhao Kang, Ming Yang, Qiang Cheng:
RAP: Scalable RPCA for Low-rank Matrix Recovery. CIKM 2016: 2113-2118 - [c5]Chong Peng, Zhao Kang, Qiang Cheng:
A Fast Factorization-Based Approach to Robust PCA. ICDM 2016: 1137-1142 - [c4]Zhao Kang, Qiang Cheng:
Top-N Recommendation with Novel Rank Approximation. SDM 2016: 126-134 - [i8]Zhao Kang, Chong Peng, Qiang Cheng:
Top-N Recommender System via Matrix Completion. CoRR abs/1601.04800 (2016) - [i7]Zhao Kang, Qiang Cheng:
Top-N Recommendation with Novel Rank Approximation. CoRR abs/1602.07783 (2016) - [i6]Zhao Kang, Chong Peng, Ming Yang, Qiang Cheng:
Top-N Recommendation on Graphs. CoRR abs/1609.08264 (2016) - [i5]Chong Peng, Zhao Kang, Qiang Chen:
A Fast Factorization-based Approach to Robust PCA. CoRR abs/1609.08677 (2016) - 2015
- [j2]Zhao Kang, Chong Peng, Jie Cheng, Qiang Cheng:
LogDet Rank Minimization with Application to Subspace Clustering. Comput. Intell. Neurosci. 2015: 824289:1-824289:10 (2015) - [j1]Zhao Kang, Chong Peng, Qiang Cheng:
Robust Subspace Clustering via Smoothed Rank Approximation. IEEE Signal Process. Lett. 22(11): 2088-2092 (2015) - [c3]Zhao Kang, Chong Peng, Qiang Cheng:
Robust Subspace Clustering via Tighter Rank Approximation. CIKM 2015: 393-401 - [c2]Zhao Kang, Chong Peng, Qiang Cheng:
Robust PCA Via Nonconvex Rank Approximation. ICDM 2015: 211-220 - [c1]Chong Peng, Zhao Kang, Huiqing Li, Qiang Cheng:
Subspace Clustering Using Log-determinant Rank Approximation. KDD 2015: 925-934 - [i4]Zhao Kang, Chong Peng, Jie Cheng, Qiang Cheng:
LogDet Rank Minimization with Application to Subspace Clustering. CoRR abs/1507.00908 (2015) - [i3]Zhao Kang, Chong Peng, Qiang Cheng:
Robust Subspace Clustering via Smoothed Rank Approximation. CoRR abs/1508.04467 (2015) - [i2]Zhao Kang, Chong Peng, Qiang Cheng:
Robust Subspace Clustering via Tighter Rank Approximation. CoRR abs/1510.08971 (2015) - [i1]Zhao Kang, Chong Peng, Qiang Cheng:
Robust PCA via Nonconvex Rank Approximation. CoRR abs/1511.05261 (2015)
Coauthor Index
[j57] [c41] [j55] [j51] [j46] [j43] [j41] [j37] [i43] [i42] [j34] [j33] [j32] [j31] [c28] [j23] [j21] [j20] [i29] [i26] [i25] [c16] [i22] [i20] [i15] [j10] [j9] [c14] [j8] [j7] [j6] [j5] [j4] [c12] [c11] [c10] [c9] [i11] [i10] [j3] [c8] [c7] [c6] [c5] [i8] [i6] [i5] [j2] [j1] [c3] [c2] [c1] [i4] [i3] [i2] [i1]
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