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Xiaofeng Zhu 0001
Person information
- affiliation: University of Electronic Science and Technology of China, School of Information and Communication Engineering, Chengdu, China
- affiliation (former): Massey University, Institute of Natural and Mathematical Sciences, Auckland, New Zealand
- affiliation (former): Guangxi Normal University, Guangxi Key Lab of Multi-source Information Mining and Security, Guilin, China
- affiliation (former): University of Pennsylvania, Perelman School of Medicine, Department of Radiology, Philadelphia, PA, USA
- affiliation (former): University of North Carolina, Department of Radiology and BRIC, Chapel Hill, NC, USA
- affiliation: Xi'an Jiaotong University, School of Mathematics and Statistics, Xi'an, China
- affiliation (PhD 2013): University of Queensland, School of Information Technology and Electrical Engineering, Brisbane, Australia
- affiliation (former): Guangxi Normal University, Department of Computer Science, Guilin, China
Other persons with the same name
- Xiaofeng Zhu — disambiguation page
- Xiaofeng Zhu 0002 — Southeast University, School of Electrical Engineering, Nanjing, China
- Xiaofeng Zhu 0003 — Case Western Reserve University, Department of Population and Quantitative Health Sciences, Cleveland, OH, USA
- Xiaofeng Zhu 0004 — Northwestern University, Evanston, IL, USA
- Xiaofeng Zhu 0005 — Jiangsu University, Faculty of Science, Zhenjiang, China
- Xiaofeng Zhu 0006 — Northeastern University, Boston, MA, USA
- Xiaofeng Zhu 0008 — Beijing Municipal Institute of Labour Protection, China
- Xiaofeng Zhu 0009 — Beijing Institute of Graphic Communication, China
- Xiaofeng Zhu 0010 — Shanghai University of Engineering Science, Advanced Vocational Technical College, China
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2020 – today
- 2025
- [j108]Yujie Mo, Heng Tao Shen, Xiaofeng Zhu:
Unsupervised multi-view graph representation learning with dual weight-net. Inf. Fusion 114: 102669 (2025) - 2024
- [j107]Yazhou Ren, Xinyue Chen, Jie Xu, Jingyu Pu, Yonghao Huang, Xiaorong Pu, Ce Zhu, Xiaofeng Zhu, Zhifeng Hao, Lifang He:
A novel federated multi-view clustering method for unaligned and incomplete data fusion. Inf. Fusion 108: 102357 (2024) - [j106]Zhengyu Lu, Junbo Ma, Zongqian Wu, Bo Zhou, Xiaofeng Zhu:
A noise-resistant graph neural network by semi-supervised contrastive learning. Inf. Sci. 658: 120001 (2024) - [j105]Zongqian Wu, Peng Zhou, Junbo Ma, Jilian Zhang, Guoqin Yuan, Xiaofeng Zhu:
Graph augmentation for node-level few-shot learning. Knowl. Based Syst. 297: 111872 (2024) - [j104]Liang Peng, Songyue Cai, Zongqian Wu, Huifang Shang, Xiaofeng Zhu, Xiaoxiao Li:
MMGPL: Multimodal Medical Data Analysis with Graph Prompt Learning. Medical Image Anal. 97: 103225 (2024) - [j103]Jinghao Xu, Chenxi Yuan, Xiaochuan Ma, Huifang Shang, Xiaoshuang Shi, Xiaofeng Zhu:
Interpretable medical deep framework by logits-constraint attention guiding graph-based multi-scale fusion for Alzheimer's disease analysis. Pattern Recognit. 152: 110450 (2024) - [j102]Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Taotao Cai, Xiaofeng Zhu, Qing Li:
FRAMU: Attention-Based Machine Unlearning Using Federated Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 36(10): 5153-5167 (2024) - [j101]Xin Liang, Yanli Ji, Wei-Shi Zheng, Wangmeng Zuo, Xiaofeng Zhu:
SV-Learner: Support-Vector Contrastive Learning for Robust Learning With Noisy Labels. IEEE Trans. Knowl. Data Eng. 36(10): 5409-5422 (2024) - [j100]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) - [j99]Liang Peng, Rongyao Hu, Fei Kong, Jiangzhang Gan, Yujie Mo, Xiaoshuang Shi, Xiaofeng Zhu:
Reverse Graph Learning for Graph Neural Network. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4530-4541 (2024) - [j98]Liang Peng, Yujie Mo, Jie Xu, Jialie Shen, Xiaoshuang Shi, Xiaoxiao Li, Heng Tao Shen, Xiaofeng Zhu:
GRLC: Graph Representation Learning With Constraints. IEEE Trans. Neural Networks Learn. Syst. 35(6): 8609-8622 (2024) - [c95]Zongqian Wu, Yujie Mo, Peng Zhou, Shangbo Yuan, Xiaofeng Zhu:
Self-Training Based Few-Shot Node Classification by Knowledge Distillation. AAAI 2024: 15988-15995 - [c94]Fei Kong, Jinhao Duan, Lichao Sun, Hao Cheng, Renjing Xu, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu:
ACT-Diffusion: Efficient Adversarial Consistency Training for One-Step Diffusion Models. CVPR 2024: 8890-8899 - [c93]Jie Xu, Yazhou Ren, Xiaolong Wang, Lei Feng, Zheng Zhang, Gang Niu, Xiaofeng Zhu:
Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios. CVPR 2024: 22957-22966 - [c92]Fei Kong, Jinhao Duan, Ruipeng Ma, Heng Tao Shen, Xiaoshuang Shi, Xiaofeng Zhu, Kaidi Xu:
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization. ICLR 2024 - [c91]Yujie Mo, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu:
Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View. ICLR 2024 - [c90]Xiaolong Wang, Ping Hu, Rongyao Hu, Xiaofeng Zhu:
GATrack: Group-Aware features for multiple object tracking. ICME 2024: 1-6 - [c89]Jincheng Huang, Jialie Shen, Xiaoshuang Shi, Xiaofeng Zhu:
On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective. ICML 2024 - [c88]Mengmeng Zhan, Zongqian Wu, Rongyao Hu, Ping Hu, Heng Tao Shen, Xiaofeng Zhu:
Towards Dynamic-Prompting Collaboration for Source-Free Domain Adaptation. IJCAI 2024: 1643-1651 - [c87]Jincheng Huang, Yujie Mo, Ping Hu, Xiaoshuang Shi, Shangbo Yuan, Zeyu Zhang, Xiaofeng Zhu:
Exploring the Role of Node Diversity in Directed Graph Representation Learning. IJCAI 2024: 2072-2080 - [c86]Yudi Huang, Yujie Mo, Yujing Liu, Ci Nie, Guoqiu Wen, Xiaofeng Zhu:
Multiplex Graph Representation Learning via Bi-level Optimization. IJCAI 2024: 2081-2089 - [c85]Caixuan Luo, Jie Xu, Yazhou Ren, Junbo Ma, Xiaofeng Zhu:
Simple Contrastive Multi-View Clustering with Data-Level Fusion. IJCAI 2024: 4697-4705 - [c84]Weiheng Fu, Meilan Xu, Jie Wu, Xiaoshuang Shi, Kang Li, Xiaofeng Zhu:
Knowledge Distillation Based Dual-Branch Network for Whole Slide Image Analysis. MLMI@MICCAI (1) 2024: 392-401 - [c83]Jin Sun, Xiaoshuang Shi, Zhiyuan Wang, Kaidi Xu, Heng Tao Shen, Xiaofeng Zhu:
Caterpillar: A Pure-MLP Architecture with Shifted-Pillars-Concatenation. ACM Multimedia 2024: 7123-7132 - [c82]Zongqian Wu, Yujing Liu, Mengmeng Zhan, Ping Hu, Xiaofeng Zhu:
Adaptive Multi-Modality Prompt Learning. ACM Multimedia 2024: 8672-8680 - [i23]Yujing Liu, Zongqian Wu, Zhengyu Lu, Ci Nie, Guoqiu Wen, Ping Hu, Xiaofeng Zhu:
Noisy Node Classification by Bi-level Optimization based Multi-teacher Distillation. CoRR abs/2404.17875 (2024) - [i22]Zhiyuan Wang, Jinhao Duan, Lu Cheng, Yue Zhang, Qingni Wang, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu:
ConU: Conformal Uncertainty in Large Language Models with Correctness Coverage Guarantees. CoRR abs/2407.00499 (2024) - 2023
- [j97]Long Chen, Chang-An Yuan, Xiao Qin, Wei Sun, Xiaofeng Zhu:
Contrastive structure and texture fusion for image inpainting. Neurocomputing 536: 1-12 (2023) - [j96]Xing Xu, Jialiang Sun, Zuo Cao, Yin Zhang, Xiaofeng Zhu, Heng Tao Shen:
TFUN: Trilinear Fusion Network for Ternary Image-Text Retrieval. Inf. Fusion 91: 327-337 (2023) - [j95]Jie Xu, Yazhou Ren, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu:
UNTIE: Clustering analysis with disentanglement in multi-view information fusion. Inf. Fusion 100: 101937 (2023) - [j94]Hangchen Xiang, Junyi Shen, Qingguo Yan, Meilian Xu, Xiaoshuang Shi, Xiaofeng Zhu:
Multi-scale representation attention based deep multiple instance learning for gigapixel whole slide image analysis. Medical Image Anal. 89: 102890 (2023) - [j93]Xiaoshuang Shi, Zhenhua Guo, Kang Li, Yun Liang, Xiaofeng Zhu:
Self-paced resistance learning against overfitting on noisy labels. Pattern Recognit. 134: 109080 (2023) - [j92]Guolin Zhang, Zehui Hu, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu:
Dynamic graph convolutional networks by semi-supervised contrastive learning. Pattern Recognit. 139: 109486 (2023) - [j91]Zhao Kang, Hongfei Liu, Jiangxin Li, Xiaofeng Zhu, Ling Tian:
Self-paced principal component analysis. Pattern Recognit. 142: 109692 (2023) - [j90]Hengxin Li, Xiaoshuang Shi, Xiaofeng Zhu, Shuihua Wang, Zheng Zhang:
FSNet: Dual Interpretable Graph Convolutional Network for Alzheimer's Disease Analysis. IEEE Trans. Emerg. Top. Comput. Intell. 7(1): 15-25 (2023) - [j89]Jie Xu, Chao Li, Liang Peng, Yazhou Ren, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu:
Adaptive Feature Projection With Distribution Alignment for Deep Incomplete Multi-View Clustering. IEEE Trans. Image Process. 32: 1354-1366 (2023) - [j88]Yujie Mo, Yuhuan Chen, Yajie Lei, Liang Peng, Xiaoshuang Shi, Changan Yuan, Xiaofeng Zhu:
Multiplex Graph Representation Learning Via Dual Correlation Reduction. IEEE Trans. Knowl. Data Eng. 35(12): 12814-12827 (2023) - [j87]Liang Peng, Nan Wang, Jie Xu, Xiaofeng Zhu, Xiaoxiao Li:
GATE: Graph CCA for Temporal Self-Supervised Learning for Label-Efficient fMRI Analysis. IEEE Trans. Medical Imaging 42(2): 391-402 (2023) - [j86]Liang Peng, Nan Wang, Nicha C. Dvornek, Xiaofeng Zhu, Xiaoxiao Li:
FedNI: Federated Graph Learning With Network Inpainting for Population-Based Disease Prediction. IEEE Trans. Medical Imaging 42(7): 2032-2043 (2023) - [j85]Xiang Guan, Yang Yang, Jingjing Li, Xiaofeng Zhu, Jingkuan Song, Heng Tao Shen:
On the Imaginary Wings: Text-Assisted Complex-Valued Fusion Network for Fine-Grained Visual Classification. IEEE Trans. Neural Networks Learn. Syst. 34(8): 5112-5121 (2023) - [c81]Yawen Ling, Jianpeng Chen, Yazhou Ren, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, Lifang He:
Dual Label-Guided Graph Refinement for Multi-View Graph Clustering. AAAI 2023: 8791-8798 - [c80]Yujie Mo, Zongqian Wu, Yuhuan Chen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu:
Multiplex Graph Representation Learning via Common and Private Information Mining. AAAI 2023: 9217-9225 - [c79]Yujie Mo, Yajie Lei, Jialie Shen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu:
Disentangled Multiplex Graph Representation Learning. ICML 2023: 24983-25005 - [c78]Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen:
A Universal Unbiased Method for Classification from Aggregate Observations. ICML 2023: 36804-36820 - [c77]Peng Zhou, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu:
Totally Dynamic Hypergraph Neural Networks. IJCAI 2023: 2476-2483 - [c76]Xuan Chen, Weiheng Fu, Tian Li, Xiaoshuang Shi, Hengtao Shen, Xiaofeng Zhu:
Co-assistant Networks for Label Correction. MICCAI (3) 2023: 159-168 - [c75]Liang Peng, Xin Wang, Xiaofeng Zhu:
Unsupervised Multiplex Graph learning with Complementary and Consistent Information. ACM Multimedia 2023: 454-462 - [c74]Yujing Liu, Zongqian Wu, Zhengyu Lu, Guoqiu Wen, Junbo Ma, Guangquan Lu, Xiaofeng Zhu:
Multi-teacher Self-training for Semi-supervised Node Classification with Noisy Labels. ACM Multimedia 2023: 2946-2954 - [c73]Xinyue Chen, Jie Xu, Yazhou Ren, Xiaorong Pu, Ce Zhu, Xiaofeng Zhu, Zhifeng Hao, Lifang He:
Federated Deep Multi-View Clustering with Global Self-Supervision. ACM Multimedia 2023: 3498-3506 - [c72]Jie Xu, Shuo Chen, Yazhou Ren, Xiaoshuang Shi, Hengtao Shen, Gang Niu, Xiaofeng Zhu:
Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration. NeurIPS 2023 - [i21]Zhenqian Wu, Xiaoyuan Li, Yazhou Ren, Xiaorong Pu, Xiaofeng Zhu, Lifang He:
Self-Paced Neutral Expression-Disentangled Learning for Facial Expression Recognition. CoRR abs/2303.11840 (2023) - [i20]Jie Xu, Gang Niu, Xiaolong Wang, Yazhou Ren, Lei Feng, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu:
Investigating and Mitigating the Side Effects of Noisy Views in Multi-view Clustering in Practical Scenarios. CoRR abs/2303.17245 (2023) - [i19]Thanveer Shaik, Xiaohui Tao, Haoran Xie, Lin Li, Xiaofeng Zhu, Qing Li:
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy. CoRR abs/2305.06360 (2023) - [i18]Jin Sun, Xiaoshuang Shi, Zhiyuan Weng, Kaidi Xu, Heng Tao Shen, Xiaofeng Zhu:
Using Caterpillar to Nibble Small-Scale Images. CoRR abs/2305.17644 (2023) - [i17]Fei Kong, Jinhao Duan, Ruipeng Ma, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu:
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization. CoRR abs/2305.18355 (2023) - [i16]Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen:
A Universal Unbiased Method for Classification from Aggregate Observations. CoRR abs/2306.11343 (2023) - [i15]Liang Peng, Xin Wang, Xiaofeng Zhu:
Unsupervised Multiplex Graph Learning with Complementary and Consistent Information. CoRR abs/2308.01606 (2023) - [i14]Thanveer Shaik, Xiaohui Tao, Lin Li, Haoran Xie, Taotao Cai, Xiaofeng Zhu, Qing Li:
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning. CoRR abs/2309.10283 (2023) - [i13]Xinyue Chen, Jie Xu, Yazhou Ren, Xiaorong Pu, Ce Zhu, Xiaofeng Zhu, Zhifeng Hao, Lifang He:
Federated Deep Multi-View Clustering with Global Self-Supervision. CoRR abs/2309.13697 (2023) - [i12]Fei Kong, Jinhao Duan, Lichao Sun, Hao Cheng, Renjing Xu, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu:
ACT: Adversarial Consistency Models. CoRR abs/2311.14097 (2023) - [i11]Zongqian Wu, Yujing Liu, Mengmeng Zhan, Jialie Shen, Ping Hu, Xiaofeng Zhu:
Adaptive Multi-Modality Prompt Learning. CoRR abs/2312.00823 (2023) - [i10]Liang Peng, Songyue Cai, Zongqian Wu, Huifang Shang, Xiaofeng Zhu, Xiaoxiao Li:
MMGPL: Multimodal Medical Data Analysis with Graph Prompt Learning. CoRR abs/2312.14574 (2023) - 2022
- [j84]Yonghua Zhu, Junbo Ma, Changan Yuan, Xiaofeng Zhu:
Interpretable learning based Dynamic Graph Convolutional Networks for Alzheimer's Disease analysis. Inf. Fusion 77: 53-61 (2022) - [j83]Rongyao Hu, Jiangzhang Gan, Xiaofeng Zhu, Tong Liu, Xiaoshuang Shi:
Multi-task multi-modality SVM for early COVID-19 Diagnosis using chest CT data. Inf. Process. Manag. 59(1): 102782 (2022) - [j82]Jiwei Wei, Yang Yang, Xing Xu, Xiaofeng Zhu, Heng Tao Shen:
Universal Weighting Metric Learning for Cross-Modal Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6534-6545 (2022) - [j81]Yifeng Zhou, Xing Xu, Fumin Shen, Xiaofeng Zhu, Heng Tao Shen:
Flow-Edge Guided Unsupervised Video Object Segmentation. IEEE Trans. Circuits Syst. Video Technol. 32(12): 8116-8127 (2022) - [j80]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) - [j79]Xiaofeng Zhu, Shichao Zhang, Yonghua Zhu, Pengfei Zhu, Yue Gao:
Unsupervised Spectral Feature Selection With Dynamic Hyper-Graph Learning. IEEE Trans. Knowl. Data Eng. 34(6): 3016-3028 (2022) - [j78]Lingling Gao, Yanli Ji, Kumie Gedamu, Xiaofeng Zhu, Xing Xu, Heng Tao Shen:
View-Invariant Human Action Recognition Via View Transformation Network (VTN). IEEE Trans. Multim. 24: 4493-4503 (2022) - [j77]Chang-an Yuan, Yonghua Zhu, Zhi Zhong, Wei Zheng, Xiaofeng Zhu:
Robust self-tuning multi-view clustering. World Wide Web 25(2): 489-512 (2022) - [j76]Zheng Wang, Yang Yang, Jingjing Li, Xiaofeng Zhu:
Universal adversarial perturbations generative network. World Wide Web 25(4): 1725-1746 (2022) - [c71]Yujie Mo, Liang Peng, Jie Xu, Xiaoshuang Shi, Xiaofeng Zhu:
Simple Unsupervised Graph Representation Learning. AAAI 2022: 7797-7805 - [c70]Jie Xu, Chao Li, Yazhou Ren, Liang Peng, Yujie Mo, Xiaoshuang Shi, Xiaofeng Zhu:
Deep Incomplete Multi-View Clustering via Mining Cluster Complementarity. AAAI 2022: 8761-8769 - [c69]Jie Xu, Huayi Tang, Yazhou Ren, Liang Peng, Xiaofeng Zhu, Lifang He:
Multi-level Feature Learning for Contrastive Multi-view Clustering. CVPR 2022: 16030-16039 - [c68]Jiangzhang Gan, Rongyao Hu, Mengmeng Zhan, Yujie Mo, Yingying Wan, Xiaofeng Zhu:
Multi-view Unsupervised Graph Representation Learning. IJCAI 2022: 2987-2993 - [c67]Zongqian Wu, Peng Zhou, Guoqiu Wen, Yingying Wan, Junbo Ma, Debo Cheng, Xiaofeng Zhu:
Information Augmentation for Few-shot Node Classification. IJCAI 2022: 3601-3607 - [c66]Tingsong Xiao, Lu Zeng, Xiaoshuang Shi, Xiaofeng Zhu, Guorong Wu:
Dual-Graph Learning Convolutional Networks for Interpretable Alzheimer's Disease Diagnosis. MICCAI (8) 2022: 406-415 - [c65]Yujie Mo, Yuhuan Chen, Liang Peng, Xiaoshuang Shi, Xiaofeng Zhu:
Simple Self-supervised Multiplex Graph Representation Learning. ACM Multimedia 2022: 3301-3309 - [c64]Rongyao Hu, Liang Peng, Jiangzhang Gan, Xiaoshuang Shi, Xiaofeng Zhu:
Complementary Graph Representation Learning for Functional Neuroimaging Identification. ACM Multimedia 2022: 3385-3393 - [i9]Liang Peng, Nan Wang, Jie Xu, Xiaofeng Zhu, Xiaoxiao Li:
GATE: Graph CCA for Temporal SElf-supervised Learning for Label-efficient fMRI Analysis. CoRR abs/2203.09034 (2022) - 2021
- [j75]Xiaofeng Zhu, Kim-Han Thung, Minjeong Kim:
Privacy-preserving Multimedia Data Analysis. Comput. J. 64(7): 991-992 (2021) - [j74]Heng Tao Shen, Xiaofeng Zhu, Zheng Zhang, Shui-Hua Wang, Yi Chen, Xing Xu, Jie Shao:
Heterogeneous data fusion for predicting mild cognitive impairment conversion. Inf. Fusion 66: 54-63 (2021) - [j73]Xiaofeng Zhu, Hongming Li, Heng Tao Shen, Zheng Zhang, Yanli Ji, Yong Fan:
Fusing functional connectivity with network nodal information for sparse network pattern learning of functional brain networks. Inf. Fusion 75: 131-139 (2021) - [j72]Chang-An Yuan, Zhi Zhong, Cong Lei, Xiaofeng Zhu, Rongyao Hu:
Adaptive reverse graph learning for robust subspace learning. Inf. Process. Manag. 58(6): 102733 (2021) - [j71]Xiaofeng Zhu, Bin Song, Feng Shi, Yanbo Chen, Rongyao Hu, Jiangzhang Gan, Wenhai Zhang, Man Li, Liye Wang, Yaozong Gao, Fei Shan, Dinggang Shen:
Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan. Medical Image Anal. 67: 101824 (2021) - [j70]Yingying Zhu, Minjeong Kim, Xiaofeng Zhu, Daniel Kaufer, Guorong Wu:
Long range early diagnosis of Alzheimer's disease using longitudinal MR imaging data. Medical Image Anal. 67: 101825 (2021) - [j69]Jiangzhang Gan, Zi-Wen Peng, Xiaofeng Zhu, Rongyao Hu, Junbo Ma, Guorong Wu:
Brain functional connectivity analysis based on multi-graph fusion. Medical Image Anal. 71: 102057 (2021) - [j68]Defu Yang, Xiaofeng Zhu, Chenggang Yan, Zi-Wen Peng, Maria Bagonis, Paul J. Laurienti, Martin Styner, Guorong Wu:
Joint hub identification for brain networks by multivariate graph inference. Medical Image Anal. 73: 102162 (2021) - [j67]Zheng Zhang, Xiaofeng Zhu, Guangming Lu, Yudong Zhang:
Probability Ordinal-Preserving Semantic Hashing for Large-Scale Image Retrieval. ACM Trans. Knowl. Discov. Data 15(3): 37:1-37:22 (2021) - [j66]Xiaofeng Zhu, Jianye Yang, Chengyuan Zhang, Shichao Zhang:
Efficient Utilization of Missing Data in Cost-Sensitive Learning. IEEE Trans. Knowl. Data Eng. 33(6): 2425-2436 (2021) - [j65]Rongyao Hu, Zi-Wen Peng, Xiaofeng Zhu, Jiangzhang Gan, Yonghua Zhu, Junbo Ma, Guorong Wu:
Multi-Band Brain Network Analysis for Functional Neuroimaging Biomarker Identification. IEEE Trans. Medical Imaging 40(12): 3843-3855 (2021) - [j64]Heng Tao Shen, Yonghua Zhu, Wei Zheng, Xiaofeng Zhu:
Half-Quadratic Minimization for Unsupervised Feature Selection on Incomplete Data. IEEE Trans. Neural Networks Learn. Syst. 32(7): 3122-3135 (2021) - [j63]Chengyuan Zhang, Jiayu Song, Xiaofeng Zhu, Lei Zhu, Shichao Zhang:
HCMSL: Hybrid Cross-modal Similarity Learning for Cross-modal Retrieval. ACM Trans. Multim. Comput. Commun. Appl. 17(1s): 2:1-2:22 (2021) - [c63]Rongyao Hu, Zhenyun Deng, Xiaofeng Zhu:
Multi-scale Graph Fusion for Co-saliency Detection. AAAI 2021: 7789-7796 - [c62]Jie Xu, Yazhou Ren, Huayi Tang, Xiaorong Pu, Xiaofeng Zhu, Ming Zeng, Lifang He:
Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering. ICCV 2021: 9214-9223 - [c61]Jingran Zhang, Xing Xu, Fumin Shen, Yazhou Yao, Jie Shao, Xiaofeng Zhu:
Video Representation Learning with Graph Contrastive Augmentation. ACM Multimedia 2021: 3043-3051 - [c60]Shuo Ma, Yanli Ji, Xing Xu, Xiaofeng Zhu:
Vision-guided Music Source Separation via a Fine-grained Cycle-Separation Network. ACM Multimedia 2021: 4202-4210 - [i8]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) - [i7]Xiaoshuang Shi, Zhenhua Guo, Fuyong Xing, Yun Liang, Xiaofeng Zhu:
Self-paced Resistance Learning against Overfitting on Noisy Labels. CoRR abs/2105.03059 (2021) - [i6]Jie Xu, Huayi Tang, Yazhou Ren, Xiaofeng Zhu, Lifang He:
Contrastive Multi-Modal Clustering. CoRR abs/2106.11193 (2021) - [i5]Zhao Kang, Hongfei Liu, Jiangxin Li, Xiaofeng Zhu, Ling Tian:
Self-paced Principal Component Analysis. CoRR abs/2106.13880 (2021) - [i4]Liang Peng, Nan Wang, Nicha C. Dvornek, Xiaofeng Zhu, Xiaoxiao Li:
FedNI: Federated Graph Learning with Network Inpainting for Population-Based Disease Prediction. CoRR abs/2112.10166 (2021) - 2020
- [j62]Lei Zhu, Jiayu Song, Xiaofeng Zhu, Chengyuan Zhang, Shichao Zhang, Xinpan Yuan, Yang Wang:
Adversarial Learning-Based Semantic Correlation Representation for Cross-Modal Retrieval. IEEE Multim. 27(4): 79-90 (2020) - [j61]Liangliang Liu, Shaowu Chen, Xiaofeng Zhu, Xing-Ming Zhao, Fang-Xiang Wu, Jianxin Wang:
Deep convolutional neural network for accurate segmentation and quantification of white matter hyperintensities. Neurocomputing 384: 231-242 (2020) - [j60]Ruili Wang, Jian Weng, Xiaofeng Zhu:
Deep understanding of big multimedia data. Neurocomputing 391: 189-190 (2020) - [j59]Xiaofeng Zhu, Shuo Shang, Minjeong Kim:
Privacy-preserving representation learning for big data. Neurocomputing 406: 293-294 (2020) - [j58]Xiaofeng Zhu, Chong-Yaw Wee, Minjeong Kim:
Deep understanding of big multimedia data. Neural Comput. Appl. 32(11): 6417-6419 (2020) - [j57]Xiaofeng Zhu, Yonghua Zhu, Wei Zheng:
Spectral rotation for deep one-step clustering. Pattern Recognit. 105: 107175 (2020) - [j56]Wei Zheng, Xiaofeng Zhu, Guoqiu Wen, Yonghua Zhu, Hao Yu, Jiangzhang Gan:
Unsupervised feature selection by self-paced learning regularization. Pattern Recognit. Lett. 132: 4-11 (2020) - [j55]Xiaofeng Zhu, Shichao Zhang, Jilian Zhang, Yonggang Li, Guangquan Lu, Yang Yang:
Sparse Graph Connectivity for Image Segmentation. ACM Trans. Knowl. Discov. Data 14(4): 46:1-46:19 (2020) - [j54]Xiaofeng Zhu, Shichao Zhang, Yonghua Zhu, Wei Zheng, Yang Yang:
Self-weighted Multi-view Fuzzy Clustering. ACM Trans. Knowl. Discov. Data 14(4): 48:1-48:17 (2020) - [j53]Rongyao Hu, Xiaofeng Zhu, Yonghua Zhu, Jiangzhang Gan:
Robust SVM with adaptive graph learning. World Wide Web 23(3): 1945-1968 (2020) - [j52]Xiaofeng Zhu, Jiangzhang Gan, Guangquan Lu, Jiaye Li, Shichao Zhang:
Spectral clustering via half-quadratic optimization. World Wide Web 23(3): 1969-1988 (2020) - [c59]Jiangzhang Gan, Xiaofeng Zhu, Rongyao Hu, Yonghua Zhu, Junbo Ma, Zi-Wen Peng, Guorong Wu:
Multi-graph Fusion for Functional Neuroimaging Biomarker Detection. IJCAI 2020: 580-586 - [c58]Junbo Ma, Xiaofeng Zhu, Defu Yang, Jiazhou Chen, Guorong Wu:
Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer's Disease Analysis. MICCAI (7) 2020: 387-396 - [c57]Liang Peng, Yang Yang, Xing Xu, Jingjing Li, Xiaofeng Zhu:
Multi-level expression guided attention network for referring expression comprehension. MMAsia 2020: 17:1-17:7 - [c56]Jiwei Wei, Yang Yang, Xing Xu, Yanli Ji, Xiaofeng Zhu, Heng Tao Shen:
Graph-based variational auto-encoder for generalized zero-shot learning. MMAsia 2020: 30:1-30:7 - [i3]Xiaofeng Zhu, Bin Song, Feng Shi, Yanbo Chen, Rongyao Hu, Jiangzhang Gan, Wenhai Zhang, Man Li, Liye Wang, Yaozong Gao, Fei Shan, Dinggang Shen:
Joint Prediction and Time Estimation of COVID-19 Developing Severe Symptoms using Chest CT Scan. CoRR abs/2005.03405 (2020)
2010 – 2019
- 2019
- [j51]Tao Tong, Xiaofeng Zhu, Tingting Du:
Connected graph decomposition for spectral clustering. Multim. Tools Appl. 78(23): 33247-33259 (2019) - [j50]Tong Liu, Jingting Zhu, Jukai Zhou, Yongxin Zhu, Xiaofeng Zhu:
Initialization-similarity clustering algorithm. Multim. Tools Appl. 78(23): 33279-33296 (2019) - [j49]Jialin Peng, Xiaofeng Zhu, Ye Wang, Le An, Dinggang Shen:
Structured sparsity regularized multiple kernel learning for Alzheimer's disease diagnosis. Pattern Recognit. 88: 370-382 (2019) - [j48]Yu Zhang, Han Zhang, Xiaobo Chen, Mingxia Liu, Xiaofeng Zhu, Seong-Whan Lee, Dinggang Shen:
Strength and similarity guided group-level brain functional network construction for MCI diagnosis. Pattern Recognit. 88: 421-430 (2019) - [j47]Xiaofeng Zhu, Shichao Zhang, Yonggang Li, Jilian Zhang, Lifeng Yang, Yue Fang:
Low-Rank Sparse Subspace for Spectral Clustering. IEEE Trans. Knowl. Data Eng. 31(8): 1532-1543 (2019) - [j46]Xiaofeng Zhu, Shichao Zhang, Wei He, Rongyao Hu, Cong Lei, Pengfei Zhu:
One-Step Multi-View Spectral Clustering. IEEE Trans. Knowl. Data Eng. 31(10): 2022-2034 (2019) - [j45]Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Daniel Kaufer, Guorong Wu:
Dynamic Hyper-Graph Inference Framework for Computer-Assisted Diagnosis of Neurodegenerative Diseases. IEEE Trans. Medical Imaging 38(2): 608-616 (2019) - [j44]Xiaofeng Zhu, Rongyao Hu, Cong Lei, Kim-Han Thung, Wei Zheng, Can Wang:
Low-rank hypergraph feature selection for multi-output regression. World Wide Web 22(2): 517-531 (2019) - [j43]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Group sparse reduced rank regression for neuroimaging genetic study. World Wide Web 22(2): 673-688 (2019) - [j42]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Low-rank dimensionality reduction for multi-modality neurodegenerative disease identification. World Wide Web 22(2): 907-925 (2019) - [c55]Xiaofeng Zhu:
Prediction of Mild Cognitive Impairment Conversion Using Auxiliary Information. IJCAI 2019: 4475-4481 - [c54]Xiaofeng Zhu, Dinggang Shen:
Robust and Discriminative Brain Genome Association Study. MICCAI (4) 2019: 456-464 - [c53]Defu Yang, Chenggang Yan, Feiping Nie, Xiaofeng Zhu, Md Asadullah Turja, Leo Charles Peek Zsembik, Martin Styner, Guorong Wu:
Joint Identification of Network Hub Nodes by Multivariate Graph Inference. MICCAI (3) 2019: 590-598 - [c52]Minjeong Kim, Xiaofeng Zhu, Zi-Wen Peng, Peipeng Liang, Daniel Kaufer, Paul J. Laurienti, Guorong Wu:
Constructing Multi-scale Connectome Atlas by Learning Graph Laplacian of Common Network. MICCAI (3) 2019: 727-735 - [e1]Jingkuan Song, Xiaofeng Zhu:
Web and Big Data - APWeb-WAIM 2019 International Workshops, KGMA and DSEA, Chengdu, China, August 1-3, 2019, Revised Selected Papers. Lecture Notes in Computer Science 11809, Springer 2019, ISBN 978-3-030-33981-4 [contents] - [i2]Yongqing Huo, Xiaofeng Zhu:
High dynamic range image forensics using cnn. CoRR abs/1902.10938 (2019) - 2018
- [j41]Cong Lei, Xiaofeng Zhu:
Unsupervised feature selection via local structure learning and sparse learning. Multim. Tools Appl. 77(22): 29605-29622 (2018) - [j40]Lin Wu, Xiaofeng Zhu, Tao Tong:
Global and local clustering with kNN and local PCA. Multim. Tools Appl. 77(22): 29727-29738 (2018) - [j39]Wei Zheng, Xiaofeng Zhu, Yonghua Zhu, Rongyao Hu, Cong Lei:
Dynamic graph learning for spectral feature selection. Multim. Tools Appl. 77(22): 29739-29755 (2018) - [j38]Xiaofeng Zhu, Weihong Zhang, Yong Fan:
A Robust Reduced Rank Graph Regression Method for Neuroimaging Genetic Analysis. Neuroinformatics 16(3-4): 351-361 (2018) - [j37]Jingkuan Song, Lianli Gao, Li Liu, Xiaofeng Zhu, Nicu Sebe:
Quantization-based hashing: a general framework for scalable image and video retrieval. Pattern Recognit. 75: 175-187 (2018) - [j36]Xiaofeng Zhu, Jie Shao, Jilian Zhang:
Pattern discovery from multi-source data. Pattern Recognit. Lett. 109: 1-3 (2018) - [j35]Xiaofeng Zhu, Shichao Zhang, Rongyao Hu, Yonghua Zhu, Jingkuan Song:
Local and Global Structure Preservation for Robust Unsupervised Spectral Feature Selection. IEEE Trans. Knowl. Data Eng. 30(3): 517-529 (2018) - [j34]Shichao Zhang, Xuelong Li, Ming Zong, Xiaofeng Zhu, Ruili Wang:
Efficient kNN Classification With Different Numbers of Nearest Neighbors. IEEE Trans. Neural Networks Learn. Syst. 29(5): 1774-1785 (2018) - [j33]Xiaofeng Zhu, Gerard Sanroma, Jilian Zhang, Brent C. Munsell:
Editorial: Deep Mining Big Social Data. World Wide Web 21(6): 1449-1452 (2018) - [c51]Xiaofeng Zhu, Hongming Li, Yong Fan:
Parameter-Free Centralized Multi-Task Learning for Characterizing Developmental Sex Differences in Resting State Functional Connectivity. AAAI 2018: 2660-2668 - [c50]Wei Zheng, Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang:
Robust Feature Selection on Incomplete Data. IJCAI 2018: 3191-3197 - [c49]Xiaofeng Zhu, Cong Lei, Hao Yu, Yonggang Li, Jiangzhang Gan, Shichao Zhang:
Robust Graph Dimensionality Reduction. IJCAI 2018: 3257-3263 - [c48]Yonghua Zhu, Xiaofeng Zhu, Wei Zheng:
Robust Multi-view Learning via Half-quadratic Minimization. IJCAI 2018: 3278-3284 - [c47]Hongming Li, Xiaofeng Zhu, Yong Fan:
Identification of Multi-scale Hierarchical Brain Functional Networks Using Deep Matrix Factorization. MICCAI (3) 2018: 223-231 - [r1]Xiaofeng Zhu:
Multimedia Tagging. Encyclopedia of Database Systems (2nd ed.) 2018 - [i1]Hongming Li, Xiaofeng Zhu, Yong Fan:
Identification of multi-scale hierarchical brain functional networks using deep matrix factorization. CoRR abs/1809.05557 (2018) - 2017
- [j32]Rongyao Hu, Xiaofeng Zhu, Debo Cheng, Wei He, Yan Yan, Jingkuan Song, Shichao Zhang:
Graph self-representation method for unsupervised feature selection. Neurocomputing 220: 130-137 (2017) - [j31]Wei He, Xiaofeng Zhu, Debo Cheng, Rongyao Hu, Shichao Zhang:
Unsupervised feature selection for visual classification via feature-representation property. Neurocomputing 236: 5-13 (2017) - [j30]Xiaofeng Zhu, Xudong Luo, Chen Xu:
Editorial learning for multimodal data. Neurocomputing 253: 1-5 (2017) - [j29]Xiaofeng Zhu, Heung-Il Suk, Li Wang, Seong-Whan Lee, Dinggang Shen:
A novel relational regularization feature selection method for joint regression and classification in AD diagnosis. Medical Image Anal. 38: 205-214 (2017) - [j28]Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Feiping Nie, Brent C. Munsell, Guorong Wu:
Multi-modal classification of neurodegenerative disease by progressive graph-based transductive learning. Medical Image Anal. 39: 218-230 (2017) - [j27]Xiaofeng Zhu, Zhi Jin, Rongrong Ji:
Learning high-dimensional multimedia data. Multim. Syst. 23(3): 281-283 (2017) - [j26]Wei He, Xiaofeng Zhu, Debo Cheng, Rongyao Hu, Shichao Zhang:
Low-rank unsupervised graph feature selection via feature self-representation. Multim. Tools Appl. 76(9): 12149-12164 (2017) - [j25]Xiaofeng Zhu, Heung-Il Suk, Heng Huang, Dinggang Shen:
Low-Rank Graph-Regularized Structured Sparse Regression for Identifying Genetic Biomarkers. IEEE Trans. Big Data 3(4): 405-414 (2017) - [j24]Shichao Zhang, Xuelong Li, Ming Zong, Xiaofeng Zhu, Debo Cheng:
Learning k for kNN Classification. ACM Trans. Intell. Syst. Technol. 8(3): 43:1-43:19 (2017) - [j23]Xiaofeng Zhu, Xuelong Li, Shichao Zhang, Zongben Xu, Litao Yu, Can Wang:
Graph PCA Hashing for Similarity Search. IEEE Trans. Multim. 19(9): 2033-2044 (2017) - [j22]Xiaofeng Zhu, Xuelong Li, Shichao Zhang, Chunhua Ju, Xindong Wu:
Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 28(6): 1263-1275 (2017) - [c46]Xiaofeng Zhu, Wei He, Yonggang Li, Yang Yang, Shichao Zhang, Rongyao Hu, Yonghua Zhu:
One-Step Spectral Clustering via Dynamically Learning Affinity Matrix and Subspace. AAAI 2017: 2963-2969 - [c45]Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang, Rongyao Hu, Wei He:
Adaptive Hypergraph Learning for Unsupervised Feature Selection. IJCAI 2017: 3581-3587 - [c44]Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Daniel Kaufer, Guorong Wu:
A Novel Dynamic Hyper-graph Inference Framework for Computer Assisted Diagnosis of Neuro-Diseases. IPMI 2017: 158-169 - [c43]Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Jin Yan, Guorong Wu:
A Tensor Statistical Model for Quantifying Dynamic Functional Connectivity. IPMI 2017: 398-410 - [c42]Qian Wang, Shaoyu Wang, Xiaofeng Zhu, Tianyi Liu, Zachary Humphrey, Vladimir Ghukasyan, Mike Conway, Erik Scott, Giulia Fragola, Kira Bradford, Mark J. Zylka, Ashok K. Krishnamurthy, Jason L. Stein, Guorong Wu:
Accurate and High Throughput Cell Segmentation Method for Mouse Brain Nuclei Using Cascaded Convolutional Neural Network. Patch-MI@MICCAI 2017: 55-62 - [c41]Xiaofeng Zhu, Kim-Han Thung, Ehsan Adeli, Yu Zhang, Dinggang Shen:
Maximum Mean Discrepancy Based Multiple Kernel Learning for Incomplete Multimodality Neuroimaging Data. MICCAI (3) 2017: 72-80 - [c40]Tao Zhou, Kim-Han Thung, Xiaofeng Zhu, Dinggang Shen:
Feature Learning and Fusion of Multimodality Neuroimaging and Genetic Data for Multi-status Dementia Diagnosis. MLMI@MICCAI 2017: 132-140 - [c39]Yu Zhang, Han Zhang, Xiaobo Chen, Mingxia Liu, Xiaofeng Zhu, Dinggang Shen:
Inter-subject Similarity Guided Brain Network Modeling for MCI Diagnosis. MLMI@MICCAI 2017: 168-175 - [c38]Yingying Zhu, Minjeong Kim, Xiaofeng Zhu, Jin Yan, Daniel Kaufer, Guorong Wu:
Personalized Diagnosis for Alzheimer's Disease. MICCAI (3) 2017: 205-213 - 2016
- [j21]Xiaofeng Zhu, Feng Lu, Chen Xu, Rongrong Ji:
Learning for medical imaging. Neurocomputing 195: 1-5 (2016) - [j20]Wenjing Li, Yingzhou Bi, Xiaofeng Zhu, Chang-an Yuan, Xiang-bo Zhang:
Hybrid swarm intelligent parallel algorithm research based on multi-core clusters. Microprocess. Microsystems 47: 151-160 (2016) - [j19]Xiaofeng Zhu, Heung-Il Suk, Seong-Whan Lee, Dinggang Shen:
Subspace Regularized Sparse Multitask Learning for Multiclass Neurodegenerative Disease Identification. IEEE Trans. Biomed. Eng. 63(3): 607-618 (2016) - [j18]Xiaofeng Zhu, Xuelong Li, Shichao Zhang:
Block-Row Sparse Multiview Multilabel Learning for Image Classification. IEEE Trans. Cybern. 46(2): 450-461 (2016) - [c37]Shichao Zhang, Lifeng Yang, Yonggang Li, Yan Luo, Xiaofeng Zhu:
Low-Rank Feature Reduction and Sample Selection for Multi-output Regression. ADMA 2016: 126-141 - [c36]Wei He, Xiaofeng Zhu, Yonggang Li, Rongyao Hu, Yonghua Zhu, Shichao Zhang:
Unsupervised Hypergraph Feature Selection with Low-Rank and Self-Representation Constraints. ADMA 2016: 172-187 - [c35]Rongyao Hu, Xiaofeng Zhu, Wei He, Jilian Zhang, Shichao Zhang:
Supervised Feature Selection by Robust Sparse Reduced-Rank Regression. ADMA 2016: 700-713 - [c34]Jailin Peng, Le An, Xiaofeng Zhu, Yan Jin, Dinggang Shen:
Structured Sparse Kernel Learning for Imaging Genetics Based Alzheimer's Disease Diagnosis. MICCAI (2) 2016: 70-78 - [c33]Xiaofeng Zhu, Heung-Il Suk, Kim-Han Thung, Yingying Zhu, Guorong Wu, Dinggang Shen:
Joint Discriminative and Representative Feature Selection for Alzheimer's Disease Diagnosis. MLMI@MICCAI 2016: 77-85 - [c32]Yingying Zhu, Xiaofeng Zhu, Han Zhang, Wei Gao, Dinggang Shen, Guorong Wu:
Reveal Consistent Spatial-Temporal Patterns from Dynamic Functional Connectivity for Autism Spectrum Disorder Identification. MICCAI (1) 2016: 106-114 - [c31]Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Dinggang Shen, Guorong Wu:
Early Diagnosis of Alzheimer's Disease by Joint Feature Selection and Classification on Temporally Structured Support Vector Machine. MICCAI (1) 2016: 264-272 - [c30]Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Chen Zu, Feiping Nie, Dinggang Shen, Guorong Wu:
Progressive Graph-Based Transductive Learning for Multi-modal Classification of Brain Disorder Disease. MICCAI (1) 2016: 291-299 - [c29]Xiaofeng Zhu, Kim-Han Thung, Jun Zhang, Dinggang Shen:
Fast Neuroimaging-Based Retrieval for Alzheimer's Disease Analysis. MLMI@MICCAI 2016: 313-321 - [c28]Xiaofeng Zhu, Heung-Il Suk, Heng Huang, Dinggang Shen:
Structured Sparse Low-Rank Regression Model for Brain-Wide and Genome-Wide Associations. MICCAI (1) 2016: 344-352 - 2015
- [j17]Xiaofeng Zhu, Qing Xie, Yonghua Zhu, Xingyi Liu, Shichao Zhang:
Multi-view multi-sparsity kernel reconstruction for multi-class image classification. Neurocomputing 169: 43-49 (2015) - [j16]Yang Yang, Zheng-Jun Zha, Yue Gao, Xiaofeng Zhu, Tat-Seng Chua:
Corrections to "Exploiting Web Images for Semantic Video Indexing Via Robust Sample-Specific Loss". IEEE Trans. Multim. 17(2): 256 (2015) - [c27]Gerard Sanroma, Oualid M. Benkarim, Gemma Piella, Guorong Wu, Xiaofeng Zhu, Dinggang Shen, Miguel Ángel González Ballester:
Discriminative Dimensionality Reduction for Patch-Based Label Fusion. MLMMI@ICML 2015: 94-103 - [c26]Guorong Wu, Xiaofeng Zhu, Qian Wang, Dinggang Shen:
Image Super-Resolution by Supervised Adaption of Patchwise Self-similarity from High-Resolution Image. Patch-MI@MICCAI 2015: 10-18 - [c25]Xiaofeng Zhu, Heung-Il Suk, Yonghua Zhu, Kim-Han Thung, Guorong Wu, Dinggang Shen:
Multi-view Classification for Identification of Alzheimer's Disease. MLMI 2015: 255-262 - [c24]Lianli Gao, Jingkuan Song, Junming Shao, Xiaofeng Zhu, Heng Tao Shen:
Zero-shot Image Categorization by Image Correlation Exploration. ICMR 2015: 487-490 - 2014
- [j15]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
A novel matrix-similarity based loss function for joint regression and classification in AD diagnosis. NeuroImage 100: 91-105 (2014) - [j14]Xiaofeng Zhu, Lei Zhang, Zi Huang:
A Sparse Embedding and Least Variance Encoding Approach to Hashing. IEEE Trans. Image Process. 23(9): 3737-3750 (2014) - [j13]Yang Yang, Zheng-Jun Zha, Yue Gao, Xiaofeng Zhu, Tat-Seng Chua:
Exploiting Web Images for Semantic Video Indexing Via Robust Sample-Specific Loss. IEEE Trans. Multim. 16(6): 1677-1689 (2014) - [c23]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Matrix-Similarity Based Loss Function and Feature Selection for Alzheimer's Disease Diagnosis. CVPR 2014: 3089-3096 - [c22]Hongyun Cai, Zi Huang, Xiaofeng Zhu, Qing Zhang, Xuefei Li:
Multi-Output Regression with Tag Correlation Analysis for Effective Image Tagging. DASFAA (2) 2014: 31-46 - [c21]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Sparse Discriminative Feature Selection for Multi-class Alzheimer's Disease Classification. MLMI 2014: 157-164 - [c20]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
Multi-modality Canonical Feature Selection for Alzheimer's Disease Diagnosis. MICCAI (2) 2014: 162-169 - [c19]Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen:
A Novel Multi-relation Regularization Method for Regression and Classification in AD Diagnosis. MICCAI (3) 2014: 401-408 - 2013
- [j12]Xiaofeng Zhu, Zi Huang, Yang Yang, Heng Tao Shen, Changsheng Xu, Jiebo Luo:
Self-taught dimensionality reduction on the high-dimensional small-sized data. Pattern Recognit. 46(1): 215-229 (2013) - [j11]Xiaofeng Zhu, Zi Huang, Jiangtao Cui, Heng Tao Shen:
Video-to-Shot Tag Propagation by Graph Sparse Group Lasso. IEEE Trans. Multim. 15(3): 633-646 (2013) - [j10]Xiaofeng Zhu, Zi Huang, Hong Cheng, Jiangtao Cui, Heng Tao Shen:
Sparse hashing for fast multimedia search. ACM Trans. Inf. Syst. 31(2): 9 (2013) - [c18]Xiaofeng Zhu, Jilian Zhang, Shichao Zhang:
Mixed-Norm Regression for Visual Classification. ADMA (1) 2013: 265-276 - [c17]Jilian Zhang, Xiaofeng Zhu, Xianxian Li, Shichao Zhang:
Mining Item Popularity for Recommender Systems. ADMA (2) 2013: 372-383 - [c16]Xin Zhao, Xue Li, Chaoyi Pang, Xiaofeng Zhu, Quan Z. Sheng:
Online human gesture recognition from motion data streams. ACM Multimedia 2013: 23-32 - [c15]Xiaofeng Zhu, Zi Huang, Heng Tao Shen, Xin Zhao:
Linear cross-modal hashing for efficient multimedia search. ACM Multimedia 2013: 143-152 - [c14]Xiaofeng Zhu, Zi Huang, Xindong Wu:
Multi-View Visual Classification via a Mixed-Norm Regularizer. PAKDD (1) 2013: 520-531 - [c13]Wei Ding, Xindong Wu, Shichao Zhang, Xiaofeng Zhu:
Feature Selection by Joint Graph Sparse Coding. SDM 2013: 803-811 - 2012
- [j9]Xiaofeng Zhu, Zi Huang, Heng Tao Shen, Jian Cheng, Changsheng Xu:
Dimensionality reduction by Mixed Kernel Canonical Correlation Analysis. Pattern Recognit. 45(8): 3003-3016 (2012) - 2011
- [j8]Shichao Zhang, Zhi Jin, Xiaofeng Zhu:
Missing data imputation by utilizing information within incomplete instances. J. Syst. Softw. 84(3): 452-459 (2011) - [j7]Xiaofeng Zhu, Shichao Zhang, Zhi Jin, Zili Zhang, Zhuoming Xu:
Missing Value Estimation for Mixed-Attribute Data Sets. IEEE Trans. Knowl. Data Eng. 23(1): 110-121 (2011) - [c12]Xiaofeng Zhu, Zi Huang, Heng Tao Shen:
Video-to-shot tag allocation by weighted sparse group lasso. ACM Multimedia 2011: 1501-1504 - [c11]Heng Tao Shen, Jie Shao, Zi Huang, Yang Yang, Jingkuan Song, Jiajun Liu, Xiaofeng Zhu:
UQMSG Experiments for TRECVID 2011. TRECVID 2011
2000 – 2009
- 2009
- [j6]Yongsong Qin, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
POP algorithm: Kernel-based imputation to treat missing values in knowledge discovery from databases. Expert Syst. Appl. 36(2): 2794-2804 (2009) - [j5]Yongsong Qin, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Estimating confidence intervals for structural differences between contrast groups with missing data. Expert Syst. Appl. 36(3): 6431-6438 (2009) - [j4]Shichao Zhang, Zhi Jin, Xiaofeng Zhu, Jilian Zhang:
Missing Data Analysis: A Kernel-Based Multi-Imputation Approach. Trans. Comput. Sci. 3: 122-142 (2009) - 2008
- [j3]Shichao Zhang, Zifang Huang, Jilian Zhang, Xiaofeng Zhu:
Mining follow-up correlation patterns from time-related databases. Knowl. Inf. Syst. 14(1): 81-100 (2008) - [j2]Shichao Zhang, Jilian Zhang, Xiaofeng Zhu, Yongsong Qin, Chengqi Zhang:
Missing Value Imputation Based on Data Clustering. Trans. Comput. Sci. 1: 128-138 (2008) - [c10]Shichao Zhang, Zhi Jin, Xiaofeng Zhu:
NIIA: Nonparametric Iterative Imputation Algorithm. PRICAI 2008: 544-555 - 2007
- [j1]Yongsong Qin, Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Semi-parametric optimization for missing data imputation. Appl. Intell. 27(1): 79-88 (2007) - [c9]Jilian Zhang, Shichao Zhang, Xiaofeng Zhu, Xindong Wu, Chengqi Zhang:
Measuring the Uncertainty of Differences for Contrasting Groups. AAAI 2007: 1920-1921 - [c8]Xiaofeng Zhu, Shichao Zhang, Jilian Zhang, Chengqi Zhang:
Cost-Sensitive Imputing Missing Values with Ordering. AAAI 2007: 1922-1923 - [c7]Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Cost-Time Sensitive Decision Tree with Missing Values. KSEM 2007: 447-459 - [c6]Chengqi Zhang, Xiaofeng Zhu, Jilian Zhang, Yongsong Qin, Shichao Zhang:
GBKII: An Imputation Method for Missing Values. PAKDD 2007: 1080-1087 - 2006
- [c5]Shichao Zhang, Yongsong Qin, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Kernel-Based Multi-Imputation for Missing Data. AMT 2006: 106-111 - [c4]Huijing Huang, Yongsong Qin, Xiaofeng Zhu, Jilian Zhang, Shichao Zhang:
Difference Detection Between Two Contrast Sets. DaWaK 2006: 481-490 - [c3]Shichao Zhang, Jilian Zhang, Xiaofeng Zhu, Zifang Huang:
Identifying Follow-Correlation Itemset-Pairs. ICDM 2006: 765-774 - [c2]Shichao Zhang, Yongsong Qin, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang:
Optimized Parameters for Missing Data Imputation. PRICAI 2006: 1010-1016 - 2005
- [c1]Ailing Ni, Xiaofeng Zhu, Chengqi Zhang:
Any-Cost Discovery: Learning Optimal Classification Rules. Australian Conference on Artificial Intelligence 2005: 123-132
Coauthor Index
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