Representative Publications


[1] UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup,
Zongbo Han, Zhipeng Liang, Fan Yang, Liu Liu, Lanqing Li, Yatao Bian, Peilin Zhao, Bingzhe Wu*, Changqing Zhang*, Jianhua Yao*,
The Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS) (CCF推荐A类会议), 2022. [LINK][CODE]

[2] Trusted Multi-View Classification with Dynamic Evidential Fusion,
Zongbo Han, Changqing Zhang* Huazhu Fu and Joey Tianyi Zhou,
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI) (CCF推荐A类期刊, SCI一区期刊, IF: 16.389), 2022
[LINK][CODE]

[3] Multimodal Dynamics: Dynamical Fusion for Trustworthy Multimodal Classification,
Zongbo Han, Fan Yang, Junzhou Huang, Changqing Zhang* and Jianhua Yao*,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (CCF推荐A类会议), 2022.

[4] Trustworthy Long-tailed Classification,
Bolian Li, Zongbo Han, Haining Li, Huazhu Fu and Changqing Zhang*,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (CCF推荐A类会议), 2022. [LINK]

[5] Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions,
Huan Ma, Zongbo Han, Changqing Zhang*, Huazhu Fu, Joey Tianyi Zhou and Qinghua Hu,
The Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) (CCF推荐A类会议), 2021. [LINK][CODE]

[6] Trusted Multi-View Classification,
Zongbo Han, Changqing Zhang*, Huazhu Fu, Joey Tianyi Zhou,
The 9th International Conference on Learning Representations (ICLR) (机器学习顶级会议), 2021. [LINK][CODE]

[7] Uncertainty-Aware Multi-View Representation Learning,
Yu Geng, Zongbo Han, Changqing Zhang*, Qinghua Hu,
The Thirty-Five AAAI Conference on Artificial Intelligence (AAAI) (CCF推荐A类会议), 2020. [LINK][CODE]

[8] Deep Partial Multi-View Learning,
Changqing Zhang, Yajie Cui, Zongbo Han, Joey Tianyi Zhou, Huazhu Fu and Qinghua Hu,
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI) (CCF推荐A类期刊, SCI一区期刊, IF: 17.861),
DOI: 10.1109/TPAMI.2020.3037734. [LINK][CODE]

[9] Generalized Latent Multi-View Subspace Clustering,
Changqing Zhang, Huazhu Fu, Qinghua Hu, Xiaochun Cao, Yuan Xie, Dacheng Tao and Dong Xu,
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI) (CCF推荐A类期刊, SCI一区期刊, IF: 17.861),
DOI: 10.1109/TPAMI.2018.2877660. [LINK][CODE]

[10] A Fast Adaptive k-means with No Bounds,
Shuyin Xia, Daowan Peng, Deyu Meng, Changqing Zhang, Guoyin Wang, Elisabeth Giem, Wei Wei and Zizhong Chen,
IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE T-PAMI) (CCF推荐A类期刊, SCI一区期刊, IF: 17.861),
DOI: 10.1109/TPAMI.2020.3008694. [LINK]

[11] Tensorized Multi-View Subspace Representation Learning,
Changqing Zhang, Huazhu Fu, Jing Wang, Wen Li, Xiaochun Cao, Qinghua Hu,
International Journal of Computer Vision (IJCV) (CCF推荐A类期刊, SCI一区期刊), [LINK]

[12] CPM-Nets: Cross Partial Multi-View Networks,
Changqing Zhang, Zongbo Han, Yajie Cui, Huazhu Fu, Joey Tianyi Zhou, and Qinghua Hu,
The Thirty-third Conference on Neural Information Processing Systems (NeurIPS) (CCF推荐A类会议, Spotlight Paper, ~3%), 2019. [LINK][CODE]

[13] AE^2-Nets: Autoencoder in Autoencoder Networks,
Changqing Zhang, Yeqing Liu, Huazhu Fu,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (CCF推荐A类会议, Oral Paper, ~5.6%), 2019. [LINK][CODE]

[14] Latent Multi-view Subspace Clustering,
Changqing Zhang, Qinghua Hu, Huazhu Fu, Pengfei Zhu and Xiaochun Cao,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)(CCF推荐A类会议, Spotlight Paper, ~8%), 2017: 4333-4341.
[LINK][CODE][DATA]

[15] Low-Rank Tensor Constrained Multiview Subspace Clustering,
Changqing Zhang, Huazhu Fu,Si Liu,Guangcan Liu and Xiaochun Cao,
IEEE International Conference on Computer Vision (ICCV)(CCF推荐A类会议), 2015: 1582--1590. [LINK] [CODE][DATA]

[16] Diversity-induced Multi-View Subspace Clustering,
Xiaochun Cao,Changqing Zhang*, Huazhu Fu, Si Liu and Hua Zhang,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)(CCF推荐A类会议), 2015: 586-94. [LINK] [CODE][DATA]

[17] Flexible Multi-view Dimensionality co-Reduction,
Changqing Zhang, Huazhu Fu, Qinghua Hu, Pengfei Zhu and Xiaochun Cao,
IEEE Transactions on Image Processing (IEEE T-IP)(CCF推荐A类期刊, SCI一区期刊, IF: 6.790), 2017, 26 (2): 648-659. [LINK][CODE][DATA]

[18] Hybrid Noise Oriented Multi-Label Learning,
Changqing Zhang, Ziwei Yu, Huazhu Fu, Pengfei Zhu, Lei Chen and Qinghua Hu,
IEEE Transactions on Cybernetics (IEEE T-CYB) (CCF推荐B类期刊, SCI一区期刊, IF: 10.387), 2019. [LINK]

[19] Infant Brain Development Prediction with Latent Partial Multi-View Representation Learning,
Changqing Zhang, Ehsan Adeli, Zhengwang Wu, Gang Li, Weili Lin and Dinggang Shen,
IEEE Transactions on Medical Imaging (IEEE T-MI) (CCF推荐B类期刊, SCI二区期刊, IF: 7.816),
DOI: 10.1109/TMI.2018.2874964. [LINK]

[20] FISH-MML: Fisher-HSIC Multi-View Metric Learning,
Changqing Zhang, Yeqing Liu, Qinghua Hu, Yue Liu, Xinwang Liu and Pengfei Zhu,
The Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI) (CCF推荐A类会议), 2018: 3054-3060. [LINK][CODE]

[21] Latent Semantic Aware Multi-View Multi-label Classification,
Changqing Zhang, Ziwei Yu, Qinghua Hu, Pengfei Zhu, Xinwang Liu and Xiaobo Wang,
The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI) (CCF推荐A类会议), 2018: 4414-4421. [LINK]

[22] Multi-Layer Multi-View Classification for Alzheimer's Disease Diagnosis,
Changqing Zhang, Ehsan Adeli, Tao Zhou, Xiaobo Chen and Dinggang Shen,
The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI) (CCF推荐A类会议), 2018: 4406-4413. [LINK]

[23] Saliency-aware Nonparametric Foreground Annotation based on Weakly Labeled Data,
Xiaochun Cao, Changqing Zhang*, Huazhu Fu, Xiaojie Guo and Qi Tian.
IEEE Transactions on Neural Networks and Learning Systems (IEEE T-NNLS) (CCF推荐B类期刊, SCI一区期刊, IF: 11.683), 2016, 27(6): 1253-1265. [LINK]

[24] Constrained Multi-view Video Face Clustering,
Xiaochun Cao, Changqing Zhang*, Chengju Zhou, Huazhu Fu and Hassan Foroosh,
IEEE Transactions on Image Processing (IEEE T-IP)(CCF推荐A类期刊, SCI一区期刊, IF: 6.790), 2015, 24(11): 4381-4393. [LINK][CODE]

[25] SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning,
Junbing Li, Changqing Zhang*, Pengfei Zhu, Baoyuan Wu, Lei Chen and Qinghua Hu,
European Conference on Computer Vision (ECCV) (CCF推荐B类会议), 2020. [LINK]

[26] Deep-LIFT:Deep Label Specific Feature Learning for Image Annotation,
Junbing Li, Changqing Zhang*, Pengfei Zhu, Baoyuan Wu, Lei Chen and Qinghua Hu,
IEEE Transactions on Cybernetics (IEEE T-CYB) (CCF推荐B类期刊, SCI一区期刊, IF: 11.079), 2021. [LINK]