. I received the PhD degree supervised by
from Zhengzhou University in 2018. I worked one year as a visiting scholar at Visual Computing Groups (VCG) in University of Portsmouth, UK.
Computer Vision, Pattern Recognition, Machine Learning, Artificial Intelligence.
Xiaoqiang Yan, Yiqiao Mao, Yangdong Ye and Hui Yu: Incremental Multiview Clustering With Continual Information Bottleneck Method. IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSMC). Accepted, 2024.
Xiaoqiang Yan, Zhixiang Jin, Yiqiao Mao, Yangdong Ye and Hui Yu: Differentiable self-supervised clustering with intrinsic interpretability. Neural Networks (NN). 2024, 179: 106542.
Shizhe Hu, Zhengzheng Lou, Xiaoqiang Yan, and Yangdong Ye. A Survey on Information Bottleneck. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). (2024) Accepted.
Yiqiao Mao, Xiaoqiang Yan, Zirui Hu, Xuguang Zhang, Yangdong Ye. Memory-aware Continual Learning with Multi-modal Social Media Streams for Unsupervised Disaster Classification. Advanced Engineering Informatics (AEI), 2024. [CODE]
Yiqiao Mao, Xiaoqiang Yan, Shizhe Hu, and Yangdong Ye. Contrastive Cross-Modal Clustering with Twin Network. Pattern Recognition (PR). 2024 Accepted. [CODE]
Yiqiao Mao, Xiaoqiang Yan, Jiaming Liu, and Yangdong Ye. ConGMC: Consistency-Guided Multimodal Clustering via Mutual Information Maximin. IEEE Transactions on Multimedia (TMM). (2023) Accepted. [CODE]
Xiaoqiang Yan, Yiqiao Mao, Yangdong Ye and Hui Yu: Cross-modal Clustering with Deep Correlated Information Bottleneck Method. IEEE Transactions on Neural Networks and Learning Systems (TNNLS). Accepted, 2023.
Xiaoqiang Yan, Yiqiao Mao, Mingyuan Li, Yangdong Ye and Hui Yu: Multi-task Image Clustering via Deep Information Bottleneck. IEEE Transactions on Cybernetics (TCYB). Accepted, 2023.
Xiaoqiang Yan, Xiangyu Yu, Shizhe Hu, and Yangdong Ye: Mutual Boost Network for attributed graph clustering. Expert Systems With Applications. 2023, 229(Part A): 120479. [PDF][CODE]
Shizhe Hu, Zenglin Shi, Xiaoqiang Yan, Zhengzheng Lou, and Yangdong Ye*: Multi-view Clustering with Propagating Information Bottleneck. IEEE Transactions on Neural Networks and Learning Systems (TNNLS). Accepted, 2023.
Xiaoqiang Yan, Yiqiao Mao, Yangdong Ye, Hui Yu, and Fei-Yue Wang: Explanation Guided Cross-modal Social Image Clustering.Information Sciences.(2022) Accepted.[PDF]
Xiaoqiang Yan, Kaiyuan Shi, Yangdong Ye, and Hui Yu: Deep Correlation Mining for Multi-task Image Clustering. Expert Systems With Applications. 2021, Accepted.
Xiaoqiang Yan, Shizhe Hu, Yiqiao Mao, Yangdong Ye, and Hui Yu: Deep Multi-view Learning Methods: A Review. Neurocomputing. 2021, Accepted. [PDF]
Xiaoqiang Yan, Yangdong Ye, Xueying Qiu, Hui Yu: Synergetic information bottleneck for joint multi-view and ensemble clustering. Information Fusion. 2020, 56:15-27. [PDF]
Xiaoqiang Yan, Yangdong Ye, Xueying Qiu, Milos Manic, Hui Yu: CMIB:Unsupervised Image Object Categorization in Multiple Visual Contexts. IEEE Transaction on Industrial Informatics (IEEE TII). 2020, 16(6):3974-3986. [PDF]
Xiaoqiang Yan, Zhengzheng Lou, Shizhe Hu, Yangdong Ye: Multi-task information bottleneck co-clustering for unsupervised cross-view human action categorization. ACM Transactions on Knowledge Discovery from Data (ACM TKDD). 2020, 14(2):1-23. [PDF]
Mingming Zhang, Xiaoqiang Yan, Shizhe Hu, Yangdong Ye: An Information Maximization Multi-task Clustering Method for Egocentric Temporal Segmentation. Applied Soft Computing. 2020, Accepted. [PDF]
Shizhe Hu, Xiaoqiang Yan, Yangdong Ye: Joint Specific and Correlated Information Exploration for Multi-view Action Clustering. Information Sciences. 2020, Accepted. [PDF]
Shizhe Hu, Xiaoqiang Yan, Yangdong Ye: Dynamic Auto-weighted Multi-view Co-clustering. Pattern Recognition (PR). 2019, Accepted. [PDF]
Shizhe Hu, Xiaoqiang Yan, Yangdong Ye: Multi-task Image Clustering through Correlation Propagation. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE). 2019, Accepted. [PDF]
Xiaoqiang Yan, Yangdong Ye, Yiqiao Mao, Hui Yu: Shared-Private Information Bottleneck Method for Cross-Modal Clustering. IEEE Access. 2019, 7, 36045-36056. [PDF]
Xiaoqiang Yan, Yangdong Ye, Zhengzheng Lou: Unsupervised video categorization based on multivariate information bottleneck method. Knowledge-Based Systems (KBS). 2015, 84, 34-45. [PDF]
Xiaoqiang Yan, Zhixiang Jin, Fengshou Han, Yangdong Ye: Differentiable Information Bottleneck for Deterministic Multi-view Clustering. IEEE Conference on Computer Vision and Pattern Recognition (IEEE CVPR), 2024, Accept.
Xiaoqiang Yan, Yingtao Gan, Yangdong Ye, Hui Yu: Live and Learn: Continual Action Clustering with Incremental Views. In AAAI Conference on Artificial Intelligence (AAAI). 2024, Accept.
Yiqiao Mao*, Xiaoqiang Yan*, Qiang Guo, Yangdong Ye: Deep Mutual Information Maximin for Cross-Modal Clustering. AAAI Conference on Artificial Intelligence (AAAI). 2021, Accepted. (* means equal contribution.)
Xiaoqiang Yan, Yiqiao Mao, Shizhe Hu, Yangdong Ye: Heterogeneous Dual-Task Clustering with Visual-Textual Information. SIAM International Conference on Data Mining (SDM). 2020, 658-666. [PDF]
Xiaoqiang Yan, Shizhe Hu, Yangdong Ye: Multi-task Clustering of Human Actions by Sharing Information. IEEE Conference on Computer Vision and Pattern Recognition (IEEE CVPR). 2017, 6401-6409. [PDF]
Xiaoqiang Yan, Yangdong Ye, Xueying Qiu: Unsupervised Human Action Categorization with Consensus Information Bottleneck Method. International Joint Conference on Artificial Intelligence (IJCAI). 2016, 2245-2251. [PDF]
Zhengzheng Lou, Yangdong Ye, Xiaoqiang Yan: The Multi-Feature Information Bottleneck with Application to Unsupervised Image Categorization. International Joint Conference on Artificial Intelligence (IJCAI). 2013,1508-1515. [PDF]