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Selected Conference Papers:

2024

  1. [AAAI] Yu Feng, Weixuan Liang, Xinhang Wan, Jiyuan Liu, Suyuan Liu, Qian Qu, Renxiang Guan, Huiying Xu,Xinwang Liu: Incremental Nyström-based Multiple Kernel Clustering. AAAI 2025. (CCF Rank A)

  2. [AAAI] Pei Zhang, Yuangang Pan, Siwei Wang, Shengju Yu, Huiying Xu, En Zhu, Xinwang Liu, Ivor Tsang: Max-Mahalanobis Anchors Guidance for Multi-View Clustering. AAAI 2025. (CCF Rank A)

  3. [AAAI] Renxiang Guan, Wenxuan Tu, Siwei Wang, Jiyuan Liu, Dayu Hu, Junhong Li, Yu Feng, Baili Xiao, Chang Tang, Xinwang Liu: Structure-Adaptive Multi-View Graph Clustering for Remote Sensing Data. AAAI 2025. (CCF Rank A)

  4. [NeurIPS] Haoyuan Qin, Chennan Ma, Mian Deng, Zhengzhu Liu, Songzhu Mei, Xinwang Liu, Cheng Wang, Siqi Shen: The Dormant Neuron Phenomenon in Multi-Agent Reinforcement Learning Value Factorization . NeurIPS 2024. (CCF Rank A)

  5. [NeurIPS] Fangdi Wang, Siwei Wang, Jiaqi Jin, jingtao Hu, Suyuan Liu, Xihong Yang, Xinwang Liu, En Zhu: Evaluate then cooperate: Shapley-based View Cooperation Enhancement for Multi-view Clustering . NeurIPS 2024. (CCF Rank A)

  6. [NeurIPS] Yue Liu, Shihao Zhu, Jun Xia, Yingwei Ma, Jian Ma, Wenliang Zhong, Xinwang Liu, Shengju Yu, Kejun Zhang: End-to-end Learnable Clustering for Intent Learning in Recommendation . NeurIPS 2024. (CCF Rank A)

  7. [NeurIPS] Suyuan Liu, Siwei Wang, Ke Liang, Junpu Zhang, Zhibin Dong, Tianrui Liu, En Zhu, Xinwang Liu, Kunlun He: Alleviate Anchor-Shift: Explore Blind Spots with Cross-View Reconstruction for Incomplete Multi-View Clustering . NeurIPS 2024. (CCF Rank A)

  8. [NeurIPS] Ke Liang, Yue Liu，Hao Liu, Lingyuan Meng, Suyuan Liu, Siwei Wang, Sihang, Zhou, Xinwang Liu: Clustering then Propagation: Select Better Anchors for Knowledge Graph Embedding . NeurIPS 2024. (CCF Rank A)

  9. [NDSS] Hao Yu, Chuan Ma, Xinhang Wang, Jun Wang, Tao Xiang, Meng Shen, Xinwang Liu: DShield: Defending against Backdoor Attacks on Graph Neural Networks via Discrepancy Learning. NDSS 2025. (CCF Rank A)

  10. [ACM MM] Ke Liang, Lingyuan Meng, Yue Liu, Meng Liu, Wei Wei, Siwei Wang, Suyuan Liu, Wenxuan Tu, Sihang Zhou, Xinwang Liu: Simple Yet Effective: Structure Guided Pre-trained Transformer for Multi-modal Knowledge Graph Reasoning. ACM MM 2024. (CCF Rank A)

  11. [ACM MM] Huimin Ma, Siwei Wang, Shengju Yu, Suyuan Liu, Jun-Jie Huang, Huijun Wu, Xinwang Liu, En Zhu: Automatic and Aligned Anchor Learning Strategy for Multi-View Clustering. ACM MM 2024. (CCF Rank A)

  12. [ACM MM] Dayu Hu, Suyuan Liu, Jun Wang, Junpu Zhang, Siwei Wang, Xingchen Hu, Xinzhong Zhu, Chang Tang, Xinwang Liu: Reliable Attribute-missing Multi-view Clustering with Instance-level and Feature-level Cooperative Imputation. ACM MM 2024. (CCF Rank A)

  13. [ACM MM] Xihong Yang, Erxue Min, Ke Liang, Yue Liu, Siwei Wang, Sihang Zhou, Huijun Wu, Xinwang Liu, En Zhu: GraphLearner: Graph Node Clustering with Fully Learnable Augmentation. ACM MM 2024. (CCF Rank A)

  14. [ACM MM] Qian Qu, Xinhang Wan, Weixuan Liang, Jiyuan Liu, Yu Feng, Huiying Xu, Xinwang Liu, En Zhu: A Lightweight Anchor-Based Incremental Framework for Multi-view Clustering. ACM MM 2024. (CCF Rank A)

  15. [ACM MM] Xiao He, Chang Tang, Xinwang Liu, Chuankun Li, Shan An and Zhenglai Li: Heterogeneous Graph Guided Contrastive Learning for Spatially Resolved Transcriptomics Data. ACM MM 2024. (CCF Rank A)

  16. [ACM MM] Fangdi Wang, Siwei Wang, Tianrui Liu, Jiaqi Jin, Zhibin Dong, Xihong Yang, Yu Feng, Xinzhong Zhu, Xinwang Liu, En Zhu: View Gap Matters: Cross-view Topology and Information Decoupling for Multi-view Clustering. ACM MM 2024. (CCF Rank A)

  17. [ACM MM] Jiaxin Zhang, Yiqi Wang, Xihong Yang, Siwei Wang, Yu Feng, Yu Shi, Ruichao Ren, En Zhu, Xinwang Liu: Test-Time Training on Graphs with Large Language Models (LLMs). ACM MM 2024. (CCF Rank A)

  18. [ICML] Xinhang Wan, Jiyuan Liu, Xinwang Liu, Yi Wen, Hao Yu, Siwei Wang, Shengju Yu, Tianjiao Wan, Jun Wang, En Zhu: Decouple then Classify: A Dynamic Multi-view Labeling Strategy with Shared and Specific Information. ICML 2024. (CCF Rank A)

  19. [ICML] Shengju Yu, Zhibin Dong, Siwei Wang, Xinhang Wan, Yue Liu, Weixuan Liang, Pei Zhang, Wenxuan Tu, Xinwang Liu: Towards Resource-friendly, Extensible and Stable Incomplete Multi-view Clustering. ICML 2024. (CCF Rank A)

  20. [ICML] Weixuan Liang, Xinwang Liu, En Zhu, Shengju Yu, Huiying Xu, Xinzhong Zhu: Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation. ICML 2024. (CCF Rank A)

  21. [CVPR] Suyuan Liu, Ke Liang, Zhibin Dong, Siwei Wang, Xihong Yang, Sihang Zhou, En Zhu, Xinwang Liu: Learn from View Correlation: An Anchor Enhancement Strategy for Multi-view Clustering. CVPR 2024. (CCF Rank A)

  22. [ICLR] Meng Liu, Yue Liu, Ke Liang, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu: Deep Temporal Graph Clustering. ICLR 2024. (THU Rank A)

  23. [AAAI] Wenxuan Tu, Renxiang Guan, Sihang Zhou, Chuan Ma, Xin Peng, Zhiping Cai, Zhe Liu, Jieren Cheng, Xinwang Liu: Attribute-missing Graph Clustering Network. AAAI 2024. (CCF Rank A)

  24. [AAAI] Suyuan Liu, Junpu Zhang, Yi Wen, Xihong Yang, Siwei Wang, Yi Zhang, En Zhu, Chang Tang, Long Zhao, Xinwang Liu: Sample-level Cross-view Similarity Learning for Incomplete Multi-view Clustering. AAAI 2024. (CCF Rank A)

  25. [AAAI] Ke Liang, Sihang Zhou, Meng Liu, Yue Liu, Wenxuan Tu, Yi Zhang, Liming Fang, Zhe Liu, Xinwang Liu: Hawkes-enhanced Spatial-Temporal Hypergraph Contrastive Learning based on Criminal Correlations. AAAI 2024. (CCF Rank A)

  26. [AAAI] Ke Liang, Lingyuan Meng, Sihang Zhou, Wenxuan Tu, Siwei Wang, Yue Liu, Meng Liu, Long Zhao, Xiangjun Dong, Xinwang Liu: MINES: Message Intercommunication for Inductive Relation Reasoning over Neighbor-Enhanced Subgraphs. AAAI 2024. (CCF Rank A)

  27. [AAAI] Shengju Yu, Siwei Wang, Pei Zhang, Miao Wang, Ziming Wang, Zhe Liu, Liming Fang, En Zhu, Xinwang Liu: DVSAI: Diverse View-Shared Anchors Based Incomplete Multi-view Clustering. AAAI 2024. (CCF Rank A)

2023

  1. [NeurIPS] Siqi Shen, Chennan Ma, Chao Li, Weiquan Liu, Yongquan Fu, Songzhu Mei, Xinwang Liu, Cheng Wang: RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value Factorization . NeurIPS 2023. (CCF Rank A)

  2. [NeurIPS] Yufeng Zhang, Jialu Pan, Wanwei Liu, Zhenbang Chen, Xinwang Liu, Ji Wang, Kenli Li: On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions . NeurIPS 2023. (CCF Rank A)

  3. [ACM MM] Yue Liu, Ke Liang, Jun Xia, Xihong Yang, Sihang Zhou, Meng Liu, Xinwang Liu, and Stan Z. Li: Reinforcement Graph Clustering with Unknown Cluster Number. ACM MM 2023. (CCF Rank A)

  4. [ACM MM] Jingcan Duan, Pei Zhang, Siwei Wang, Jingtao Hu, Hu Jin, Jiaxin Zhang, Haifang Zhou, Xinwang Liu: Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive Learning. ACM MM 2023. (CCF Rank A)

  5. [ACM MM] Xin Zou, Chang Tang, Xiao Zheng, Zhenglai Li, Xiao He, Shan An, and Xinwang Liu: DPNET: Dynamic Poly-attention Network for Trustworthy Multi-modal Classification. ACM MM 2023. (CCF Rank A)

  6. [ACM MM] Yi Wen, Siwei Wang, Ke Liang, Weixuan Liang, Xinhang Wan, Xinwang Liu, Suyuan Liu, Jiyuan Liu, and En Zhu: Scalable Incomplete Multi-View Clustering with Structure Alignment. ACM MM 2023. (CCF Rank A)

  7. [ACM MM] Yi Wen, Suyuan Liu, Xinhang Wan, Siwei Wang, Ke Liang, Xinwang Liu, Xihong Yang, and Pei Zhang: Efficient Multi-View Graph Clustering with Local and Global Structure Preservation. ACM MM 2023. (CCF Rank A)

  8. [ACM MM] Xihong Yang, Cheng Tan, Yue Liu, Ke Liang, Siwei Wang, Sihang Zhou, Jun Xia, Stan Z. Li, Xinwang Liu, En Zhu: CONVERT: Contrastive Graph Clustering with Reliable Augmentation. ACM MM 2023. (CCF Rank A)

  9. [ACM MM] Xihong Yang, Jiaqi Jin, Siwei Wang, Ke Liang, Yue Liu, Yi Wen, Suyuan Liu, Sihang Zhou, Xinwang Liu, En Zhu: DealMVC: Dual Contrastive Calibration for Multi-view Clustering. ACM MM 2023. (CCF Rank A)

  10. [ACM MM] Meng Liu, Ke Liang, Dayu Hu, Hao Yu, Yue Liu, Lingyuan Meng, Wenxuan Tu, Sihang Zhou, Xinwang Liu: TMac: Temporal Multi-Modal Graph Learning for Acoustic Event Classification. ACM MM 2023. (CCF Rank A)

  11. [ICCV] Zhibin Dong, Jiaqi Jin, Siwei Wang, Xinwang Liu, En Zhu: Cross-view Topology Based Consistent and Complementary Information for Deep Multi-view Clustering. ICCV 2023. (CCF Rank A)

  12. [CVPR] Jiaqi Jin, Siwei Wang, Zhibin Dong, Xinwang Liu, En Zhu: Deep Incomplete Multi-view Clustering with Cross-view Partial Sample and Prototype Alignment. CVPR 2023. (CCF Rank A)

  13. [ICML] Weixuan Liang, Xinwang Liu, Yong Liu, Chuan Ma, Yunping Zhao, Zhe Liu, En Zhu: Consistency of Multiple Kernel Clustering. ICML 2023. (CCF Rank A)

  14. [ICML] Yue Liu, Ke Liang, Jun Xia, Sihang Zhou, Xihong Yang, Xinwang Liu, Stan Z. Li: Dink-Net: Neural Clustering on Large Graphs. ICML 2023. (CCF Rank A)

  15. [SIGIR] Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu: Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning. SIGIR 2023. (CCF Rank A)

  16. [AAAI] Xinhang Wan, Xinwang Liu, Jiyuan Liu, Siwei Wang ,Yi Wen, Weixuan Liang, En Zhu, Zhe Liu, Lu Zhou: Auto-weighted Multi-view Clustering for Large-scale Data. AAAI 2023. (CCF Rank A)

  17. [AAAI] Xihong Yang, Yue Liu, Sihang Zhou, Siwei Wang, Wenxuan Tu, Qun Zheng, Xinwang Liu, Liming Fang, En Zhu: Cluster-guided Contrastive Graph Clustering Network. AAAI 2023 (CCF Rank A)

  18. [AAAI] Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Zhen Wang, Ke Liang, Wenxuan Tu, Liang Li, Jingcan Duan, Cancan Chen: Hard Sample Aware Network for Contrastive Deep Graph Clustering. AAAI 2023 (CCF Rank A)[PDF][Code]

  19. [AAAI] Pei Zhang, Siwei Wang, Liang Li, Changwang Zhang, Xinwang Liu, En Zhu, Zhe Liu, Lu Zhou, Lei Luo: Let the data choose: Flexible and Diverse Anchor Graph Fusion for Scalable Multi-view Clustering. AAAI 2023. (CCF Rank A)

2022

  1. [NeurIPS] Siwei Wang, Xinwang Liu, Suyuan Liu, Jiaqi Jin, Wenxuan Tu, Xinzhong Zhu, En Zhu: Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching Correspondences . NeurIPS 2022. (CCF Rank A)

  2. [NeurIPS] Weixuan Liang, Xinwang Liu, Yong Liu, Sihang Zhou, Jun-Jie Huang, Siwei Wang, Jiyuan Liu, Yi Zhang, En Zhu: Stability and Generalization of Kernel Clustering: from Single Kernel to Multiple Kernel. NeurIPS 2022. (CCF Rank A)[PDF]

  3. [NeurIPS] Siqi Shen, Mengwei Qiu, Liu Jun, Weiquan Liu, Yongquan Fu, Xinwang Liu, Cheng Wang: ResQ: A Residual Q Function-based Approach for Multi-Agent Reinforcement Learning Value Factorization. NeurIPS 2022. (CCF Rank A)

  4. [ACM MM] Xinhang Wan, Jiyuan Liu, Weixuan Liang, Xinwang Liu, Yi Wen and En Zhu: Continual Multi-view Clustering. ACM MM 2022. (CCF Rank A)[PDF]

  5. [ACM MM] Yi Zhang, Weixuan Liang, Xinwang Liu, Sisi Dai, Siwei Wang, Liyang Xu and En Zhu: Sample Weighted Multiple Kernel K-means via min-max optimization. ACM MM 2022. (CCF Rank A)[PDF]

  6. [ACM MM] Guang Yu, Siqi Wang, Zhiping Cai, Xinwang Liu and Chengkun Wu: Effective Video Abnormal Event Detection by Learning A Consistency-Aware High-Level Feature Extractor. ACM MM 2022. (CCF Rank A)[PDF]

  7. [ACM MM] Tiejian Zhang, Xinwang Liu, En Zhu, Sihang Zhou, Zhibin Dong: Efficient Anchor Learning-based Multi-view Clustering -- A Late Fusion Method. ACM MM 2022. (CCF Rank A)[PDF]

  8. [ACM MM] Junpu Zhang, Liang Li, Siwei Wang, Jiyuan Liu, Yue Liu, Xinwang Liu and En Zhu: Multiple Kernel Clustering with Dual Noise Minimization. ACM MM 2022. (CCF Rank A)[PDF]

  9. [IJCAI] Wenxuan Tu, Sihang Zhou, Xinwang Liu, Yue Liu, Zhiping Cai, En Zhu, Changwang Zhang, Jieren Cheng: Initializing Then Refining: A Simple Graph Attribute Imputation Network. IJCAI 2022. (CCF Rank A)[PDF]

  10. [IJCAI] Lei Gong,  Sihang Zhou, Wenxuan Tu, Xinwang Liu: Attributed Graph Clustering with Dual Redundancy Reduction. IJCAI 2022. (CCF Rank A)[PDF]

  11. [CVPR] Siwei Wang, Xinwang Liu, Li Liu, Wenxuan Tu, Xinzhong Zhu, Jiyuan Liu, Sihang Zhou, En Zhu: Highly-efficient Incomplete Large-scale Multi-view Clustering with Consensus Bipartite Graph. CVPR 2022. (CCF Rank A)

  12. [CVPR] Guang Yu, Siqi Wang, Zhiping Cai, Xinwang Liu, Chuanfu Xu, Chengkun Wu: Deep Anomaly Discovery from Unlabeled Videos via Normality Advantage and Self-Paced Refinement. CVPR 2022. (CCF Rank A)[PDF]

  13. [CVPR] Yao Duan, Chenyang Zhu, Yuqing Lan, Renjiao Yi, Xinwang Liu, Kai Xu: DisARM: Displacement Aware Relation Module for 3D Detection. CVPR 2022. (CCF Rank A)

  14. [AAAI] Yue Liu, Wenxuan Tu, Sihang Zhou, Xinwang Liu, Linxuan Song, Xihong Yang, En Zhu: Deep Graph Clustering via Dual Correlation Reduction. AAAI 2022. (CCF Rank A)[PDF][Code]

  15. [AAAI] Suyuan Liu, Siwei Wang, Pei Zhang, Kai Xu, Xinwang Liu, Changwang Zhang, Feng Gao: Efficient One-pass Multi-view Subspace Clustering with Consensus Anchors. AAAI 2022. (CCF Rank A)[PDF]

  16. [AAAI] Yi Zhang, Xinwang Liu, Jiyuan Liu, Sisi Dai, Changwang Zhang, Kai Xu, En Zhu: Fusion Multiple Kernel K-means. AAAI 2022. (CCF Rank A)[PDF]

  17. [AAAI] Weixuan Liang, Xinwang Liu, Sihang Zhou, Jiyuan Liu, Siwei Wang, En Zhu: Robust Graph-based Multi-view Clustering. AAAI 2022. (CCF Rank A)[PDF][Code]

2021

  1. [ICCV]Jiyuan Liu, Xinwang Liu, Yuexiang Yang, Li Liu, Siqi Wang, Weixuan Liang, Jiangyong Shi: One-pass Multi-view Clustering for Large-scale Data. ICCV 2021: 12344-12353. (CCF Rank A)[PDF][Code]

  2. [ICCV] Xinwang Liu, Sihang Zhou, Li Liu, Chang Tang, Siwei Wang, Jiyuan Liu, Yi Zhang: Localized Simple Multiple Kernel K-means. ICCV 2021: 9293-9301. (CCF Rank A)[PDF][Code]

  3. [ACM MM]Yi Zhang, Xinwang Liu, Siwei Wang, Jiyuan Liu, Sisi Dai, En Zhu: One-Stage Incomplete Multi-view Clustering via Late Fusion. ACM MM 2021: 2717–2725. (CCF Rank A)[PDF][Code]

  4. [ACM MM]Mengjing Sun, Pei Zhang, Siwei Wang, Sihang Zhou, Wenxuan Tu, Xinwang Liu, En Zhu, Changjian Wang: Scalable Multi-view Subspace Clustering with Unified Anchors. ACM MM 2021: 3528–3536. (CCF Rank A)[PDF][Code]

  5. [ACM MM]Chen Zhang, Siwei Wang, Jiyuan Liu, Sihang Zhou, Pei Zhang, Xinwang Liu, En Zhu, Changwang Zhang: Multi-view Clustering via Deep Matrix Factorization and Partition Alignment. ACM MM 2021: 4156–4164. (CCF Rank A)[PDF][Code]

  6. [ACM MM] Jiyuan Liu, Xinwang Liu, Yi Zhang, Pei Zhang, Wenxuan Tu, Siwei Wang, Sihang Zhou, Weixuan Liang, Siqi Wang and Yuexiang Yang: Self-representation Subspace Clustering for Incomplete Multi-view Data. ACM MM 2021: 2726–2734. (CCF Rank A)[PDF][Code]

  7. [ICML] Xinwang Liu, Li Liu, Qing Liao, Chang Tang, Siwei Wang, Wenxuan Tu, Jiyuan Liu, Yi Zhang and En Zhu: One Pass Late Fusion Multi-view Clustering. ICML 2021: 6850-6859. (CCF Rank A)[PDF] [Code]

  8. [IJCAI] Chang Tang, Xinwang Liu, En Zhu, Lizhe Wang and Albert Zomaya: Hyperspectral Band Selection via Spatial-Spectral Weighted Region-wise Multiple Graph Fusion-Based Spectral Clustering. IJCAI 2021: 3038-3044. (CCF Rank A)[PDF]

  9. [AAAI] Jiyuan Liu, Xinwang Liu, Yuexiang Yang, Siwei Wang, Sihang Zhou: Hierarchical Multiple Kernel Clustering. AAAI 2021: 35(10), 8671-8679. (CCF Rank A)[PDF] [Code]

  10. [AAAI] Wenxuan Tu, Sihang Zhou, Xinwang Liu, Xifeng Guo, Zhiping Cai, En Zhu, and Jieren Cheng: Deep Fusion Clustering Network. AAAI 2021: 35(11), 9978-9987. (CCF Rank A)[PDF] [Code]

2020

  1. [IJCAI] Jinglin Xu, Xiangsen Zhang, Wenbin Li, Xinwang Liu, and Junwei Han: Joint Multi-view 2D Convolutional Neural Networks for 3D Object Classification. IJCAI 2020: 3202-3208. (CCF Rank A)[PDF]

  2. [AAAI] Sihang Zhou, Xinwang Liu, Jiyuan Liu, Xifeng Guo, Yawei Zhao, En Zhu, Yongping Zhai, Jianping Yin and Wen Gao: Multi-View Spectral Clustering with Optimal Neighborhood Laplacian Matrix. AAAI 2020: 34(04), 6965-6972. (CCF Rank A) [PDF] [Code]

  3. [AAAI] Chang Tang, Xinwang Liu, Xinzhong Zhu, En Zhu, Kun Sun, Pichao Wang, Lizhe Wang and Albert Zomaya: MRF: Defocus Blur Detection via Recurrently Refining Multi-scale Residual Features. AAAI 2020: 34(07), 12063-12070. (CCF Rank A)

  4. [AAAI] Chang Tang, Xinwang Liu, Xinzhong Zhu, En Zhu, Zhigang Luo, Wen Gao: CGD: Multi-view Clustering via Cross-view Graph Diffusion. AAAI 2020: 34(04), 5924-5931. (CCF Rank A)

  5. [AAAI] Li Cheng, Yijie Wang, Xinwang Liu and Bin Li: Outlier Detection Ensemble with Embedded Feature Selection. AAAI 2020: 34(04), 3503-3512. (CCF Rank A) [PDF]

  6. [AAAI] Jinglin Xu, Wenbin Li, Xinwang Liu, Dingwen Zhang, Ji Liu, Junwei Han: Embedding Deep Interaction Information for Multi-view Categorization. AAAI 2020: 34(04), 6494-6501. (CCF Rank A)

2019

  1. [NeurIPS] Siqi Wang, Yijie Zeng, Xinwang Liu, En Zhu, Jianping Yin, Chuanfu Xu, and Marius Kloft: Effective End-to-end Unsupervised Outlier Detection via Inlier Priority of Discriminative Network. NeurIPS 2019: 5962–5975 (CCF Rank A) [PDF] [Code]

  2. [AAAI] Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Chang Tang, En Zhu, Jianping Yin, Wen Gao: Efficient and Effective Incomplete Multi-view Clustering. AAAI 2019: 33(01), 4392-4399.(CCF Rank A) [PDF]

  3. [AAAI] Chang Tang, Xinwang Liu, Xinzhong Zhu, Lizhe Wang: Cross-view Local Structure Preserved Diversity and Consensus Learning for Multi-view Unsupervised Feature Selection. AAAI 2019: 33(01), 5101-5108.(CCF Rank A) [PDF]

  4. [AAAI] Siqi Wang, En Zhu, Xiping Hu, Xinwang Liu, Qiang Liu, Jianping Yin, Fei Wang: Robustness Can Be Cheap: A Highly Efficient Approach to Discover Outliers under High Outlier Ratios. AAAI 2019: 33(01), 5313-5320.(CCF Rank A) [PDF]

  5. [CVPR] Chang Tang, Xinzhong Zhu, Xinwang Liu, Lizhe Wang, Albert Zomaya: DeFusionNET: Defocus Blur Detection via Recurrently Fusing and Refining Multi-scale Deep Features. CVPR 2019: 2700-2709. (CCF Rank A) [PDF]

  6. [IJCAI] Xifeng Guo, Xinwang Liu, En Zhu and Jianping Yin: Affine Equivariant Autoencoder. IJCAI 2019: 2413-2419.(CCF Rank A) [PDF]

  7. [IJCAI] Siwei Wang, Xinwang Liu, Chang Tang, Jiyuan Liu, En Zhu, Jianping Yin, Jiangtao Hu and Jingyuan Xia: Multi-view Clustering via Late Fusion Alignment Maximization. IJCAI 2019: 3778-3784. (CCF Rank A) [PDF] [Code]

  8. [IJCAI] Wenzhang Zhuge, Chenping Hou, Xinwang Liu, Hong Tao and Dongyun Yi: Simultaneous Representation Learning and Clustering for Incomplete Multi-view Data. IJCAI 2019: 4482-4488. (CCF Rank A) [PDF]

2018

  1. [IJCAI] Xinzhong Zhu, Xinwang Liu, Miaomiao Li, En Zhu, Li Liu, Zhiping Cai, Jianping Yin, Wen Gao: Localized Incomplete Multiple Kernel k-means. IJCAI 2018: 3271-3277. (CCF Rank A) [PDF]

  2. [IJCAI] Changqing Zhang, Yeqinq Liu, Yue Liu, Qinghua Hu, Xinwang Liu, Pengfei Zhu: FISH-MML: Fisher-HSIC Multi-View Metric Learning. IJCAI 2018: 3054-3060. (CCF Rank A) [PDF]

  3. [AAAI] Pichao Wang, Wanqing Li, Jun Wan, Philip Ogunbona, and Xinwang Liu: Cooperative Training of Deep Aggregation Networks for RGB-D Action Recognition. AAAI 2018: 32(1), 7404-7411. (CCF Rank A) [PDF]

  4. [AAAI] Changqing Zhang, Ziwei Yu, Qinghua Hu, Pengfei Zhu, Xiaobo Wang, and Xinwang Liu: Latent Semantic Aware Multi-view Multi-label Classification. AAAI 2018: 32(1), 4414-4421. (CCF Rank A) [PDF]

  5. [AAAI] Hong Tao, Chenping Hou, Xinwang Liu, Dongyun Yi and Jubo Zhu: Reliable Multi-View Clustering. AAAI 2018: 32(1), 4123-4130. (CCF Rank A) [PDF]

  6. [ECCV] Melih Engin, Lei Wang, Luping Zhou, Xinwang Liu: DeepKSPD: Learning Kernel-Matrix-Based SPD Representation For Fine-Grained Image Recognition. ECCV 2018: 629-645. (CCF Rank B) [PDF]

2017

  1. [AAAI] Xinwang Liu, Miaomiao Li, Lei Wang, Yong Dou, Jianping Yin and En Zhu: Multiple Kernel k-means with Incomplete Kernels. AAAI 2017: 31 (1), 2259–2265. (CCF Rank A) [PDF]

  2. [AAAI] Xinwang Liu, Sihang Zhou, Yueqing Wang, Yong Dou, Jianping Yin and En Zhu: Optimal Neighborhood Kernel Clustering with Multiple Kernels. AAAI 2017: 31(1), 2266-2272. (CCF Rank A) [PDF] [Code]

  3. [IJCAI] Yueqing Wang, Xinwang Liu, Yong Dou: Multiple Kernel Clustering Framework with Improved Kernels. IJCAI 2017: 2999–3005. (CCF Rank A) [PDF]

  4. [IJCAI] Yueqing Wang, Xinwang Liu, Yong Dou: Approximate Large-scale Multiple Kernel k-means using Deep Neuron Network. IJCAI 2017: 3006–3012. (CCF Rank A) [PDF]

  5. [IJCAI] Xifeng Guo, Long Gao, Xinwang Liu and Jianping Yin: Improved Deep Embedded Clustering with Local Structure Preservation. IJCAI 2017: 1753-1759. (CCF Rank A) [PDF] [Code]

2016

  1. [IJCAI] Miaomiao Li, Xinwang Liu, Lei Wang, Yong Dou and Jianping Yin: Multi-view Clustering via Maximizing Local Kernel Alignment Maximization. IJCAI 2016: 1704-1710. (CCF Rank A)

  2. [AAAI] Xinwang Liu, Yong Dou, Jianping Yin, Lei Wang, En Zhu: Multiple Kernel k-means Clustering with Matrix-induced Regularization. AAAI 2016: 1888-1894. (CCF Rank A) [PDF][Code]

2015

  1. [AAAI] Xinwang Liu, Lei Wang, Jianping Yin, Yong Dou, Jian Zhang: Absent Multiple Kernel Learning. AAAI 2015: 2807-2813. (CCF Rank A) [PDF]

2014

  1. [AAAI] Xinwang Liu, Lei Wang, Jian Zhang, Jianping Yin: Sample-Adaptive Multiple Kernel Learning. AAAI 2014: 1975-1981. (CCF Rank A) [PDF]

2011

  1. [ICCV] Lingqiao Liu, Lei Wang, Xinwang Liu: In defense of soft-assignment coding. ICCV 2011: 2486-2493. (CCF Rank A) [PDF]