Publications

2019

  1. Xinwang Liu, Lei Wang, Jianping Yin and Yong Dou: Absent Multiple Kernel Learning Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence. (Accepted Jan. 2019)
  2. Xinwang Liu, Miaomiao Li, Lei Wang, Jian Zhang, En Zhu, Jianping Yin and Wen Gao: Multiple Kernel k-means with Incomplete Kernels. IEEE Transactions on Pattern Analysis and Machine Intelligence. (Accepted Jan. 2019)
  3. Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Lei Wang, Chang Tang, Jianping Yin, Dinggang Shen, Huaimin Wang and Wen Gao: Late Fusion Incomplete Multi-view Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence. (Accepted Oct. 2018)
  4. Chang Tang, Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Pichao Wang, Changqing Zhang and Lizhe Wang: Learning Joint Affinity Graph for Multi-view Subspace Clustering. IEEE Transactions on Multimedia. (Accepted Nov. 2018)
  5. Xinwang Liu, Xinzhong Zhu, Miaomiao Li, Chang Tang, En Zhu, Jianping Yin, Wen Gao: Efficient and Effective Incomplete Multi-view Clustering. AAAI 2019.
  6. 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.
  7. 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.
  8. Chang Tang, Xinzhong Zhu, Xinwang Liu, Lizhe Wang, Albert Zomaya: DeFusionNET: Defocus Blur Detection via Recurrently Fusing and Refining Multi-scale Deep Features. IEEE CVPR 2019. (CCF Rank A)
  9. Chang Tang, Xinwang Liu, Pichao Wang, Changqing Zhang, Miaomiao Li, and Lizhe Wang: Adaptive Hypergraph Embedded Semi-supervised Multilabel Image Annotation. IEEE Transactions on Multimedia. (Accepted March 2019)
  10. Chang Tang, Xinwang Liu, Miaomiao Li, Pichao Wang, and Lizhe Wang: Feature Selective Projection with Low-Rank Embedding and Dual Laplacian Regularization. IEEE Transactions on Knowledge and Data Engineering. (Accepted April 2019)
  11. Xifeng Guo, Xinwang Liu, En Zhu, Xinzhong Zhu, Miaomiao Li, Xin Xu, and Jianping Yin: Adaptive Self-paced Deep Clustering with Data Augmentation. IEEE Transactions on Knowledge and Data Engineering. (Accepted April 2019)
  12. Xifeng Guo, Xinwang Liu, En Zhu and Jianping Yin: Affine Equivariant Autoencoder. IJCAI 2019. (Accepted May 2019)
  13. 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. (Accepted May 2019)
  14. Wenzhang Zhuge, Chenping Hou, Xinwang Liu, Hong Tao and Dongyun Yi: Simultaneous Representation Learning and Clustering for Incomplete Multi-view Data. IJCAI 2019. (Accepted May 2019)
  15. Sihang Zhou, Xinwang Liu, Miaomiao Li, En Zhu, Li Liu, Changwang Zhang, and Jianping Yin: Multiple Kernel Clustering with Neighbor-Kernel Subspace Segmentation. IEEE Transactions on Neural Networks and Learning Systems. (Accepted May 2019)
  16. Sihang Zhou, En Zhu, Xinwang Liu, Tianming Zheng, Qiang Liu, Jingyuan Xia, and Jianping Yin: Subspace Segmentation-based Robust Multiple Kernel Clustering. Information Fusion. (Accepted June 2019)
  17. Yawei Zhao, En Zhu, Xinwang Liu, Deke Guo, Xinzhong Zhu, and Jianping Yin: Simultaneous Clustering and Optimization for Evolving Datasets. IEEE Transactions on Knowledge and Data Engineering. (Accepted June 2019)
  18. Chang Tang, Meiru Bian, Xinwang Liu, MiaomiaoLi, Hua Zhou, Pichao Wang, and Hailin Yin: Unsupervised feature selection via latent representation learning and manifold regularization. Neural Networks 117: 163-178 (2019) (CCF Rank B)
  19. Shaoyong Li, Chang Tang, Xinwang Liu, Yaping Liu, and Jiajia Chen: Dual graph regularized compact feature representation for unsupervised feature selection. Neurocomputing 331: 77-96 (2019) (CCF Rank C)
  20. Siwei Wang, En Zhu, Jingtao Hu, Miaomiao Li, Kaikai Zhao, Ning Hu, and Xinwang Liu: Efficient Multiple Kernel k-Means Clustering With Late Fusion. IEEE Access 7: 61109-61120 (2019)

2018

  1. Jianfeng Lu, Yun Xin, Zhao Zhang, Xinwang Liu, Kenli Li: Game-Theoretic Design of Optimal Two-Sided Rating Protocols for Service Exchange Dilemma in Crowdsourcing. IEEE Trans. Information Forensics and Security 13(11): 2801-2815 (2018). (CCF Rank A)
  2. 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)
  3. 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)
  4. Pichao Wang, Wanqing Li, Jun Wan, Philip Ogunbona, and Xinwang Liu: Cooperative Training of Deep Aggregation Networks for RGB-D Action Recognition. AAAI 2018. (CCF Rank A)
  5. Changqing Zhang, Ziwei Yu, Qinghua Hu, Pengfei Zhu, Xiaobo Wang, and Xinwang Liu: Latent Semantic Aware Multi-view Multi-label Classification. AAAI 2018. (CCF Rank A)
  6. Hong Tao, Chenping Hou, Xinwang Liu, Dongyun Yi and Jubo Zhu: Reliable Multi-View Clustering. AAAI 2018. (CCF Rank A)
  7. Melih Engin, Lei Wang, Luping Zhou, Xinwang Liu: DeepKSPD: Learning Kernel-Matrix-Based SPD Representation For Fine-Grained Image Recognition. ECCV (2) 2018: 629645. (CCF Rank B)
  8. Chang Tang, Xinzhong Zhu, Jiajia Chen, Pichao Wang, Xinwang Liu, Jie Tian: Robust graph regularized unsupervised feature selection. Expert Syst. Appl. 96: 64-76 (2018). (CCF Rank C)
  9. Qiang Wang, Yong Dou, Xinwang Liu, Fei Xia, Qi Lv, Ke Yang: Local kernel alignment based multi-view clustering using extreme learning machine. Neurocomputing 275: 1099-1111 (2018). (CCF Rank C)
  10. Jingming Xue, Sihang Zhou, Qiang Liu, Xinwang Liu, Jianping Yin: Financial time series prediction using `2,1RF-ELM. Neurocomputing 277: 176-186 (2018). (CCF Rank C)
  11. Yawei Zhao, Yuewei Ming, Xinwang Liu, En Zhu, Kaikai Zhao, Jianping Yin: Large-scale k-means clustering via variance reduction. Neurocomputing: 184-194 (2018). (CCF Rank C)
  12. Yuewei Ming, En Zhu, Mao Wang, Yongkai Ye, Xinwang Liu, Jianping Yin: DMP-ELMs: Data and model parallel extreme learning machines for large-scale learning tasks. Neurocomputing 320: 85-97 (2018). (CCF Rank C)
  13. Chang Tang, Xinwang Liu, Miaomiao Li, Pichao Wang, Jiajia Chen, Lizhe Wang, Wanqing Li: Robust unsupervised feature selection via dual self-representation and manifold regularization. Knowl.-Based Syst. 145: 109-120 (2018). (CCF Rank C)
  14. Chang Tang, Jiajia Chen, Xinwang Liu, Miaomiao Li, Pichao Wang, Minhui Wang, Peng Lu: Consensus learning guided multi-view unsupervised feature selection. Knowl.-Based Syst. 160: 49-60 (2018). (CCF Rank C)
  15. Jingming Xue, Qiang Liu, Miaomiao Li, Xinwang Liu, Yongkai Ye, Siqi Wang, Jianping Yin: Incremental multiple kernel extreme learning machine and its application in Robo-advisors. Soft Comput. 22(11): 3507-3517 (2018). (CCF Rank C)
  16. Wentao Zhao, Qian Li, Chengzhang Zhu, Jianglong Song, Xinwang Liu, Jianping Yin: Model-aware categorical data embedding: a data-driven approach. Soft Comput. 22(11): 3603-3619 (2018). (CCF Rank C)
  17. Yawei Zhao, Kai Xu, Xinwang Liu, En Zhu, Xinzhong Zhu, Jianping Yin: Triangle Lasso for Simultaneous Clustering and Optimization in Graph Datasets. IEEE Transactions on Knowledge and Data Engineering. (Accepted Aug 2018)

2017

  1. Xinwang Liu, Miaomiao Li, Lei Wang, Yong Dou, Jianping Yin and En Zhu: Multiple Kernel k-means with Incomplete Kernels. AAAI 2017. (CCF Rank A)
  2. Xinwang Liu, Sihang Zhou, Yueqing Wang, Yong Dou, Jianping Yin and En Zhu: Optimal Neighborhood Kernel Clustering with Multiple Kernels. AAAI 2017. (CCF Rank A)
  3. Yueqing Wang, Xinwang Liu, Yong Dou: Multiple Kernel Clustering Framework with Improved Kernels. IJCAI 2017. (CCF Rank A)
  4. Yueqing Wang, Xinwang Liu, Yong Dou: Approximate Large-scale Multiple Kernel k-means using Deep Neuron Network. IJCAI 2017. (CCF Rank A)
  5. Xifeng Guo, Long Gao, Xinwang Liu and Jianping Yin: Improved Deep Embedded Clustering with Local Structure Preservation. IJCAI 2017. (CCF Rank A)
  6. Ting Li, Yiming Zhang, Dongsheng Li, Xinwang Liu, Yuxing Peng: Fast Compressive Spectral Clustering. ICDM 2017: 949-954. (CCF Rank B)
  7. Xifeng Guo, Xinwang Liu, En Zhu, Jianping Yin: Deep Clustering with Convolutional Autoencoders. ICONIP (2) 2017: 373-382. (CCF Rank C)
  8. Yueqing Wang, Xinwang Liu, Yong Dou: Multiple Kernel Learning with Hybrid Kernel Alignment Maximization. Pattern Recognition 70 (2017) 104-111. (CCF Rank B)
  9. Teng Li, Yong Dou, Xinwang Liu, Yang Zhao, Qi Lv: Multiple kernel clustering with corrupted kernels. Neurocomputing 267 (2017): 447-454. (CCF Rank C)
  10. Yongkai Ye, Xinwang Liu, Qiang Liu, Jianping Yin: Consensus Kernel K-Means Clustering for Incomplete Multiview Data. Comp. Int. and Neurosc. 2017: 3961718:1-3961718:11 (2017)

2016

  1. Miaomiao Li, Xinwang Liu, Lei Wang, Yong Dou and Jianping Yin: Multi-view Clustering via Maximizing Local Kernel Alignment. International Joint Conference on Artificial Intelligence 2016: (1704-1710), July 9-16, 2016, New York, USA (CCF Rank A)
  2. Xinwang Liu, Yong Dou, Jianping Yin, Lei Wang, En Zhu: Multiple Kernel k-means Clustering with Matrix-induced Regularization. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence: (1888-1894), February 12-17, 2016, Phoenix, Arizona, USA (CCF Rank A)
  3. Yang Zhao, Yong Dou, Xinwang Liu, Teng Li: ELM based multiple kernel k-means with diversity-induced regularization. International Joint Conference on Neural Networks: (2699-2705), July 24-29, 2016, Vancouver, BC, Canada.(CCF Rank C)
  4. Yongkai Ye, Xinwang Liu, En Zhu, Jianping Yin: Co-Regularized Kernel K-Means for Multi-View Clustering. International Conference on Pattern Recognition: Dec 4-8, 2016, Cancun, Mexico. (CCF Rank C)
  5. Wei Chen, Xifeng Guo, Xinwang Liu, En Zhu, Jianping Yin: Appearance Changes Detection During Tracking. International Conference on Pattern Recognition: Dec 4-8, 2016, Cancun, Mexico. (CCF Rank C)
  6. Yule Li, Yong Dou, Xinwang Liu, Teng Li: Localized region context and object feature fusion for people head detection. ICIP 2016: 594-598. (CCF Rank C)
  7. Peidai Xie, Xinwang Liu, Jianping Yin, Yongjun Wang: Absent extreme learning machine algorithm with application to packed executable identification. Neural Computing and Application 27(1): 93-100 (2016). (CCF Rank C)
  8. Qiang Liu, Sihang Zhou, Chengzhang Zhu, Xinwang Liu, Jianping Yin: MI-ELM: Highly Efficient Multi-Instance Learning Based on Hierarchical Extreme Learning Machine, Neurocomputing 173: 1044-1053 (2016) (CCF Rank C).
  9. Yueqing Wang, Yong Dou, Xinwang Liu, Yuanwu Lei: PR-ELM: Parallel regularized extreme learning machine based on cluster. Neurocomputing 173: 1073-1081 (2016) (CCF Rank C).
  10. Sihang Zhou, Xinwang Liu, Qiang Liu, Siqi Wang, Chengzhang Zhu, Jianping Yin: Random Fourier Extreme Learning Machine with l21-norm Regularization. Neurocomputing 174: 143-153 (2016) (CCF Rank C)
  11. Qiang Wang, Yong Dou, Xinwang Liu, Qi Lv, Shijie Li: Multi-view clustering with extreme learning machine. Neurocomputing 214: 483-494 (2016) (CCF Rank C)
  12. Yang Zhao, Yong Dou, Xinwang Liu, Teng Li: A novel multi-view clustering method via low-rank and matrix-induced regularization. Neurocomputing 216: 342-350 (2016) (CCF Rank C)
  13. Teng Li, Yong Dou, Xinwang Liu: Joint diversity and graph regularization for multiple kernel k-means clustering via latent variables. Neurocomputing 218: 154-163 (2016). (CCF Rank C)

2015

  1. Xinwang Liu, Lei Wang, Jianping Yin, Yong Dou, Jian Zhang: Absent Multiple Kernel Learning. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence: (2807-2813), January 25-30, 2015, Austin, Texas, USA (CCF Rank A)
  2. Xinwang Liu, Luping Zhou, Lei Wang, Jian Zhang, Jianping Yin and Dinggang Shen: An Efficient Radius-incorporated MKL Algorithm for Alzheimer’s Disease Prediction. Pattern Recognition 48(7): 2141-2150 (2015) (CCF Rank B)
  3. Xinwang Liu, Lei Wang, Guang-Bin Huang, Jian Zhang, Jianping Yin: Multiple kernel extreme learning machine. Neurocomputing 149: 253-264 (2015) (CCF Rank C)
  4. Lei Luo, Chunhua Shen, Xinwang Liu, Chunyuan Zhang: A Computational Model of the Short-Cut Rule for 2D Shape Decomposition. IEEE Transactions on Image Processing 24(1): 273-283 (2015) (CCF Rank A)
  5. Chengzhang Zhu, Xinwang Liu, Qiang Liu, Yuewei Ming, Jianping Yin: Distance Based Multiple Kernel ELM: A Fast Multiple Kernel Learning Approach. Mathematical Problems in Engineering
  6. Hang Gao, Xinwang Liu, Yuxing Peng: Sample-based Extreme Learning Machine with Absent Data. Mathematical Problems in Engineering .

2014

  1. Xinwang Liu, Lei Wang, Jian Zhang, Jianping Yin, Huan Liu: Global and Local Structure Preservation for Feature Selection. IEEE Transactions on Neural Networks and Learning Systems 25(6): 1083-1095 (2014) (CCF Rank B)
  2. Xinwang Liu, Lei Wang, Jian Zhang, Jianping Yin: Sample-Adaptive Multiple Kernel Learning. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence: (1975-1981), July 27-31, 2014, Qu´ebec City, Qu´ebec, Canada (CCF Rank A)
  3. Xinwang Liu, Jianping Yin, Jun Long: On Radius-Incorporated Multiple Kernel Learning. Proceedings of the 11th International Conference on Modeling Decisions for Artificial Intelligence: (227-240), October 29-31, 2014, Tokyo, Japan.
  4. Shangrong Huang, Jian Zhang, Xinwang Liu, Lei Wang: A Method of Discriminative Information Preservation and In-Dimension Distance Minimization Method for Feature Selection. 22nd International Conference on Pattern Recognition: (16151620), August 24-28, 2014, Stockholm, Sweden. (CCF Rank C)
  5. Dongyan Guo, Jian Zhang, Xinwang Liu, Ying Cui, Chunxia Zhao: Multiple Kernel Learning Based Multi-View Spectral Clustering. 22nd International Conference on Pattern Recognition: (3774-3779), August 24-28, 2014, Stockholm, Sweden. (CCF Rank C)
  6. Sihang Zhou, Xinwang Liu, Chengzhang Zhu, Qiang Liu, Jianping Yin: Spectral clustering-based local and global structure preservation for feature selection. International Joint Conference on Neural Networks: (550-557), July 6-11, 2014, Beijing, China. (CCF Rank C)
  7. Chengzhang Zhu, Xinwang Liu, Sihang Zhou, Qiang Liu, Jianping Yin: A binary feature selection framework in kernel spaces. International Joint Conference on Neural Networks: (4190-4197), July 6-11, 2014, Beijing, China. (CCF Rank C)

2013

  1. Xinwang Liu, Jianping Yin, Lei Wang, Lingqiao Liu, Jun Liu, Chenping Hou, Jian Zhang: An Adaptive Approach to Learning Optimal Neighborhood Kernels. IEEE Transactions on Cybernetics 43(1): 371-384 (2013) (CCF Rank B)
  2. Xinwang Liu, Lei Wang, Jianping Yin, En Zhu, Jian Zhang: An Efficient Approach to Integrating Radius Information into Multiple Kernel Learning. IEEE Transactions on Cybernetics 43(2): 557-569 (2013) (CCF Rank B)
  3. Yubin Zhan, Jianping Yin, Xinwang Liu: Nonlinear discriminant clustering based on spectral regularization. Neural Computing and Applications 22(7-8): 1599-1608 (2013) (CCF Rank C)
  4. Bo Liu, Bin Fang, Xinwang Liu, Jie Chen, Zhenghong Huang, Xiping He: Large Margin Subspace Learning for feature selection. Pattern Recognition 46(10): 27982806 (2013) (CCF Rank B)

2012

  1. Xinwang Liu, Lei Wang, Jianping Yin, Lingqiao Liu: Incorporation of radius-info can be simple with SimpleMKL. Neurocomputing 89: 30-38 (2012) (CCF Rank C）

2011

  1. Yubin Zhan, Jianping Yin, Xinwang Liu: A Convergent Solution to Matrix Bidirectional Projection Based Feature Extraction with Application to Face Recognition. International Journal of Computational Intelligence Systems 4(5): 863-873 (2011)
  2. Lingqiao Liu, Lei Wang, Xinwang Liu: In defense of soft-assignment coding. IEEE International Conference on Computer Vision: (2486-2493), November 6-13, 2011, Barcelona, Spain. (CCF Rank A)