| 2026 | AAAI | Cross-modal Prompting for Balanced Incomplete Multi-modal Emotion Recognition. | Wenjue He, Xiaofeng Zhu, Zheng Zhang |
| 2026 | AAAI | Meta-GAIN for Missing Data Imputation. | Tao Tong, Xiaofeng Zhu, Jiangzhang Gan |
| 2026 | AAAI | COIN: Uncertainty-Guarding Selective Question Answering for Foundation Models with Provable Risk Guarantees. | Zhiyuan Wang, Jinhao Duan, Qingni Wang, Xiaofeng Zhu, Tianlong Chen, Xiaoshuang Shi, Kaidi Xu |
| 2026 | AAAI | Graph Smoothing for Enhanced Local Geometry Learning in Point Cloud Analysis. | Shangbo Yuan, Jie Xu, Ping Hu, Xiaofeng Zhu, Na Zhao |
| 2025 | AAAI | Multiplex Graph Representation Learning with Homophily and Consistency. | Yudi Huang, Ci Nie, Hongqing He, Yujie Mo, Yonghua Zhu, Guoqiu Wen, Xiaofeng Zhu |
| 2025 | AAAI | Noisy Node Classification by Bi-level Optimization Based Multi-Teacher Distillation. | Yujing Liu, Zongqian Wu, Zhengyu Lu, Ci Nie, Guoqiu Wen, Yonghua Zhu, Xiaofeng Zhu |
| 2025 | ACL | SConU: Selective Conformal Uncertainty in Large Language Models. | Zhiyuan Wang, Qingni Wang, Yue Zhang, Tianlong Chen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu |
| 2025 | CVPR | Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather. | Longyu Yang, Ping Hu, Shangbo Yuan, Lu Zhang, Jun Liu, Hengtao Shen, Xiaofeng Zhu |
| 2025 | ICCV | TruthPrInt: Mitigating Large Vision-Language Models Object Hallucination via Latent Truthful-Guided Pre-Intervention. | Jinhao Duan, Fei Kong, Hao Cheng, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu |
| 2025 | ICCV | Robust Multi-View Learning via Representation Fusion of Sample-Level Attention and Alignment of Simulated Perturbation. | Jie Xu, Na Zhao, Gang Niu, Masashi Sugiyama, Xiaofeng Zhu |
| 2025 | ICDM | Agentic Meta-Orchestrator for Multi-Task Copilots. | Xiaofeng Zhu, Yunshen Zhou |
| 2025 | ICLR | HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters. | Yujie Mo, Runpeng Yu, Xiaofeng Zhu, Xinchao Wang |
| 2025 | ICML | Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks. | Jincheng Huang, Yujie Mo, Xiaoshuang Shi, Lei Feng, Xiaofeng Zhu |
| 2025 | ICML | Navigating Semantic Drift in Task-Agnostic Class-Incremental Learning. | Fangwen Wu, Lechao Cheng, Shengeng Tang, Xiaofeng Zhu, Chaowei Fang, Dingwen Zhang, Meng Wang |
| 2025 | ICML | Rethinking Chain-of-Thought from the Perspective of Self-Training. | Zongqian Wu, Baoduo Xu, Ruochen Cui, Mengmeng Zhan, Xiaofeng Zhu, Lei Feng |
| 2025 | IJCAI | MCD-CLIP: Multi-view Chest Disease Diagnosis with Disentangled CLIP. | Songyue Cai, Yujie Mo, Liang Peng, Yucheng Xie, Tao Tong, Xiaofeng Zhu |
| 2025 | IJCAI | Graph Embedded Contrastive Learning for Multi-View Clustering. | Hongqing He, Jie Xu, Guoqiu Wen, Yazhou Ren, Na Zhao, Xiaofeng Zhu |
| 2025 | IJCAI | Meta Label Correction with Generalization Regularizer. | Tao Tong, Yujie Mo, Yucheng Xie, Songyue Cai, Xiaoshuang Shi, Xiaofeng Zhu |
| 2025 | IJCAI | Seeking Proxy Point via Stable Feature Space for Noisy Correspondence Learning. | Yucheng Xie, Songyue Cai, Tao Tong, Ping Hu, Xiaofeng Zhu |
| 2024 | AAAI | Self-Training Based Few-Shot Node Classification by Knowledge Distillation. | Zongqian Wu, Yujie Mo, Peng Zhou, Shangbo Yuan, Xiaofeng Zhu |
| 2024 | CVPR | ACT-Diffusion: Efficient Adversarial Consistency Training for One-Step Diffusion Models. | Fei Kong, Jinhao Duan, Lichao Sun, Hao Cheng, Renjing Xu, Hengtao Shen, Xiaofeng Zhu, Xiaoshuang Shi, Kaidi Xu |
| 2024 | CVPR | Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios. | Jie Xu, Yazhou Ren, Xiaolong Wang, Lei Feng, Zheng Zhang, Gang Niu, Xiaofeng Zhu |
| 2024 | EMNLP | ConU: Conformal Uncertainty in Large Language Models with Correctness Coverage Guarantees. | Zhiyuan Wang, Jinhao Duan, Lu Cheng, Yue Zhang, Qingni Wang, Xiaoshuang Shi, Kaidi Xu, Heng Tao Shen, Xiaofeng Zhu |
| 2024 | ICLR | An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization. | Fei Kong, Jinhao Duan, Ruipeng Ma, Heng Tao Shen, Xiaoshuang Shi, Xiaofeng Zhu, Kaidi Xu |
| 2024 | ICLR | Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View. | Yujie Mo, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu |
| 2024 | ICML | On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective. | Jincheng Huang, Jialie Shen, Xiaoshuang Shi, Xiaofeng Zhu |
| 2024 | IJCAI | Exploring the Role of Node Diversity in Directed Graph Representation Learning. | Jincheng Huang, Yujie Mo, Ping Hu, Xiaoshuang Shi, Shangbo Yuan, Zeyu Zhang, Xiaofeng Zhu |
| 2024 | IJCAI | Multiplex Graph Representation Learning via Bi-level Optimization. | Yudi Huang, Yujie Mo, Yujing Liu, Ci Nie, Guoqiu Wen, Xiaofeng Zhu |
| 2024 | IJCAI | Simple Contrastive Multi-View Clustering with Data-Level Fusion. | Caixuan Luo, Jie Xu, Yazhou Ren, Junbo Ma, Xiaofeng Zhu |
| 2024 | IJCAI | Towards Dynamic-Prompting Collaboration for Source-Free Domain Adaptation. | Mengmeng Zhan, Zongqian Wu, Rongyao Hu, Ping Hu, Heng Tao Shen, Xiaofeng Zhu |
| 2023 | AAAI | Dual Label-Guided Graph Refinement for Multi-View Graph Clustering. | Yawen Ling, Jianpeng Chen, Yazhou Ren, Xiaorong Pu, Jie Xu, Xiaofeng Zhu, Lifang He |
| 2023 | AAAI | Multiplex Graph Representation Learning via Common and Private Information Mining. | Yujie Mo, Zongqian Wu, Yuhuan Chen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu |
| 2023 | ICML | Disentangled Multiplex Graph Representation Learning. | Yujie Mo, Yajie Lei, Jialie Shen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu |
| 2023 | ICML | A Universal Unbiased Method for Classification from Aggregate Observations. | Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen |
| 2023 | IJCAI | Totally Dynamic Hypergraph Neural Networks. | Peng Zhou, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu |
| 2023 | MICCAI | Co-assistant Networks for Label Correction. | Xuan Chen, Weiheng Fu, Tian Li, Xiaoshuang Shi, Hengtao Shen, Xiaofeng Zhu |
| 2023 | WWW | Explicit and Implicit Semantic Ranking Framework. | Xiaofeng Zhu, Thomas Lin, Vishal Anand, Matthew Calderwood, Eric Clausen-Brown, Gord Lueck, Wen-Wai Yim, Cheng Wu |
| 2022 | AAAI | Simple Unsupervised Graph Representation Learning. | Yujie Mo, Liang Peng, Jie Xu, Xiaoshuang Shi, Xiaofeng Zhu |
| 2022 | AAAI | Deep Incomplete Multi-View Clustering via Mining Cluster Complementarity. | Jie Xu, Chao Li, Yazhou Ren, Liang Peng, Yujie Mo, Xiaoshuang Shi, Xiaofeng Zhu |
| 2022 | CVPR | Multi-level Feature Learning for Contrastive Multi-view Clustering. | Jie Xu, Huayi Tang, Yazhou Ren, Liang Peng, Xiaofeng Zhu, Lifang He |
| 2022 | IJCAI | Multi-view Unsupervised Graph Representation Learning. | Jiangzhang Gan, Rongyao Hu, Mengmeng Zhan, Yujie Mo, Yingying Wan, Xiaofeng Zhu |
| 2022 | IJCAI | Information Augmentation for Few-shot Node Classification. | Zongqian Wu, Peng Zhou, Guoqiu Wen, Yingying Wan, Junbo Ma, Debo Cheng, Xiaofeng Zhu |
| 2022 | MDM | Integrating Heterogeneous Sources for Learned Prediction of Vehicular Data Consumption. | Andi Zang, Xiaofeng Zhu, Ce Li, Fan Zhou, Goce Trajcevski |
| 2022 | MICCAI | Dual-Graph Learning Convolutional Networks for Interpretable Alzheimer's Disease Diagnosis. | Tingsong Xiao, Lu Zeng, Xiaoshuang Shi, Xiaofeng Zhu, Guorong Wu |
| 2021 | AAAI | Multi-scale Graph Fusion for Co-saliency Detection. | Rongyao Hu, Zhenyun Deng, Xiaofeng Zhu |
| 2021 | ICCV | Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering. | Jie Xu, Yazhou Ren, Huayi Tang, Xiaorong Pu, Xiaofeng Zhu, Ming Zeng, Lifang He |
| 2021 | MDM | Towards Predicting Vehicular Data Consumption. | Andi Zang, Xiaofeng Zhu, Yuxiang Guo, Fan Zhou, Goce Trajcevski |
| 2020 | IJCAI | Multi-graph Fusion for Functional Neuroimaging Biomarker Detection. | Jiangzhang Gan, Xiaofeng Zhu, Rongyao Hu, Yonghua Zhu, Junbo Ma, Zi-Wen Peng, Guorong Wu |
| 2020 | MICCAI | Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer's Disease Analysis. | Junbo Ma, Xiaofeng Zhu, Defu Yang, Jiazhou Chen, Guorong Wu |
| 2020 | WSDM | Listwise Learning to Rank by Exploring Unique Ratings. | Xiaofeng Zhu, Diego Klabjan |
| 2019 | ICMLA | Suggestion Mining from Online Reviews usingRandom Multimodel Deep Learning. | Feng Liu, Liangji Wang, Xiaofeng Zhu, Dingding Wang |
| 2019 | ICMLA | Frosting Weights for Better Continual Training. | Xiaofeng Zhu, Feng Liu, Goce Trajcevski, Dingding Wang |
| 2019 | IJCAI | Prediction of Mild Cognitive Impairment Conversion Using Auxiliary Information. | Xiaofeng Zhu |
| 2019 | MICCAI | Constructing Multi-scale Connectome Atlas by Learning Graph Laplacian of Common Network. | Minjeong Kim, Xiaofeng Zhu, Zi-Wen Peng, Peipeng Liang, Daniel Kaufer, Paul J. Laurienti, Guorong Wu |
| 2019 | MICCAI | Joint Identification of Network Hub Nodes by Multivariate Graph Inference. | Defu Yang, Chenggang Yan, Feiping Nie, Xiaofeng Zhu, Md Asadullah Turja, Leo Charles Peek Zsembik, Martin Styner, Guorong Wu |
| 2019 | MICCAI | Robust and Discriminative Brain Genome Association Study. | Xiaofeng Zhu, Dinggang Shen |
| 2018 | AAAI | Parameter-Free Centralized Multi-Task Learning for Characterizing Developmental Sex Differences in Resting State Functional Connectivity. | Xiaofeng Zhu, Hongming Li, Yong Fan |
| 2018 | IJCAI | Robust Feature Selection on Incomplete Data. | Wei Zheng, Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang |
| 2018 | IJCAI | Robust Graph Dimensionality Reduction. | Xiaofeng Zhu, Cong Lei, Hao Yu, Yonggang Li, Jiangzhang Gan, Shichao Zhang |
| 2018 | IJCAI | Robust Multi-view Learning via Half-quadratic Minimization. | Yonghua Zhu, Xiaofeng Zhu, Wei Zheng |
| 2018 | MICCAI | Identification of Multi-scale Hierarchical Brain Functional Networks Using Deep Matrix Factorization. | Hongming Li, Xiaofeng Zhu, Yong Fan |
| 2017 | AAAI | One-Step Spectral Clustering via Dynamically Learning Affinity Matrix and Subspace. | Xiaofeng Zhu, Wei He, Yonggang Li, Yang Yang, Shichao Zhang, Rongyao Hu, Yonghua Zhu |
| 2017 | IJCAI | Adaptive Hypergraph Learning for Unsupervised Feature Selection. | Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang, Rongyao Hu, Wei He |
| 2017 | IJCNLP | Semantic Document Distance Measures and Unsupervised Document Revision Detection. | Xiaofeng Zhu, Diego Klabjan, Patrick N. Bless |
| 2017 | IRI | Unsupervised Terminological Ontology Learning Based on Hierarchical Topic Modeling. | Xiaofeng Zhu, Diego Klabjan, Patrick N. Bless |
| 2017 | MICCAI | Accurate and High Throughput Cell Segmentation Method for Mouse Brain Nuclei Using Cascaded Convolutional Neural Network. | 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 |
| 2017 | MICCAI | Inter-subject Similarity Guided Brain Network Modeling for MCI Diagnosis. | Yu Zhang, Han Zhang, Xiaobo Chen, Mingxia Liu, Xiaofeng Zhu, Dinggang Shen |
| 2017 | MICCAI | Feature Learning and Fusion of Multimodality Neuroimaging and Genetic Data for Multi-status Dementia Diagnosis. | Tao Zhou, Kim-Han Thung, Xiaofeng Zhu, Dinggang Shen |
| 2017 | MICCAI | Personalized Diagnosis for Alzheimer's Disease. | Yingying Zhu, Minjeong Kim, Xiaofeng Zhu, Jin Yan, Daniel Kaufer, Guorong Wu |
| 2017 | MICCAI | Maximum Mean Discrepancy Based Multiple Kernel Learning for Incomplete Multimodality Neuroimaging Data. | Xiaofeng Zhu, Kim-Han Thung, Ehsan Adeli, Yu Zhang, Dinggang Shen |
| 2016 | ADMA | Low-Rank Feature Reduction and Sample Selection for Multi-output Regression. | Shichao Zhang, Lifeng Yang, Yonggang Li, Yan Luo, Xiaofeng Zhu |
| 2016 | ADMA | Unsupervised Hypergraph Feature Selection with Low-Rank and Self-Representation Constraints. | Wei He, Xiaofeng Zhu, Yonggang Li, Rongyao Hu, Yonghua Zhu, Shichao Zhang |
| 2016 | ADMA | Supervised Feature Selection by Robust Sparse Reduced-Rank Regression. | Rongyao Hu, Xiaofeng Zhu, Wei He, Jilian Zhang, Shichao Zhang |
| 2016 | MICCAI | Structured Sparse Kernel Learning for Imaging Genetics Based Alzheimer's Disease Diagnosis. | Jailin Peng, Le An, Xiaofeng Zhu, Yan Jin, Dinggang Shen |
| 2016 | MICCAI | Progressive Graph-Based Transductive Learning for Multi-modal Classification of Brain Disorder Disease. | Zhengxia Wang, Xiaofeng Zhu, Ehsan Adeli, Yingying Zhu, Chen Zu, Feiping Nie, Dinggang Shen, Guorong Wu |
| 2016 | MICCAI | Structured Sparse Low-Rank Regression Model for Brain-Wide and Genome-Wide Associations. | Xiaofeng Zhu, Heung-Il Suk, Heng Huang, Dinggang Shen |
| 2016 | MICCAI | Joint Discriminative and Representative Feature Selection for Alzheimer's Disease Diagnosis. | Xiaofeng Zhu, Heung-Il Suk, Kim-Han Thung, Yingying Zhu, Guorong Wu, Dinggang Shen |
| 2016 | MICCAI | Fast Neuroimaging-Based Retrieval for Alzheimer's Disease Analysis. | Xiaofeng Zhu, Kim-Han Thung, Jun Zhang, Dinggang Shen |
| 2016 | MICCAI | Early Diagnosis of Alzheimer's Disease by Joint Feature Selection and Classification on Temporally Structured Support Vector Machine. | Yingying Zhu, Xiaofeng Zhu, Minjeong Kim, Dinggang Shen, Guorong Wu |
| 2016 | MICCAI | Reveal Consistent Spatial-Temporal Patterns from Dynamic Functional Connectivity for Autism Spectrum Disorder Identification. | Yingying Zhu, Xiaofeng Zhu, Han Zhang, Wei Gao, Dinggang Shen, Guorong Wu |
| 2015 | ICDE | Finding dense and connected subgraphs in dual networks. | Yubao Wu, Ruoming Jin, Xiaofeng Zhu, Xiang Zhang |
| 2015 | ICML | Discriminative Dimensionality Reduction for Patch-Based Label Fusion. | Gerard Sanroma, Oualid M. Benkarim, Gemma Piella, Guorong Wu, Xiaofeng Zhu, Dinggang Shen, Miguel ngel Gonzlez Ballester |
| 2015 | MICCAI | Image Super-Resolution by Supervised Adaption of Patchwise Self-similarity from High-Resolution Image. | Guorong Wu, Xiaofeng Zhu, Qian Wang, Dinggang Shen |
| 2015 | MICCAI | Multi-view Classification for Identification of Alzheimer's Disease. | Xiaofeng Zhu, Heung-Il Suk, Yonghua Zhu, Kim-Han Thung, Guorong Wu, Dinggang Shen |
| 2014 | CVPR | Matrix-Similarity Based Loss Function and Feature Selection for Alzheimer's Disease Diagnosis. | Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen |
| 2014 | DASFAA | Multi-Output Regression with Tag Correlation Analysis for Effective Image Tagging. | Hongyun Cai, Zi Huang, Xiaofeng Zhu, Qing Zhang, Xuefei Li |
| 2014 | MICCAI | Multi-modality Canonical Feature Selection for Alzheimer's Disease Diagnosis. | Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen |
| 2014 | MICCAI | A Novel Multi-relation Regularization Method for Regression and Classification in AD Diagnosis. | Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen |
| 2014 | MICCAI | Sparse Discriminative Feature Selection for Multi-class Alzheimer's Disease Classification. | Xiaofeng Zhu, Heung-Il Suk, Dinggang Shen |
| 2013 | ADMA | Mining Item Popularity for Recommender Systems. | Jilian Zhang, Xiaofeng Zhu, Xianxian Li, Shichao Zhang |
| 2013 | ADMA | Mixed-Norm Regression for Visual Classification. | Xiaofeng Zhu, Jilian Zhang, Shichao Zhang |
| 2013 | PAKDD | Multi-View Visual Classification via a Mixed-Norm Regularizer. | Xiaofeng Zhu, Zi Huang, Xindong Wu |
| 2013 | SDM | Feature Selection by Joint Graph Sparse Coding. | Wei Ding, Xindong Wu, Shichao Zhang, Xiaofeng Zhu |
| 2011 | PSB | Systems Biology Analyses of Gene Expression and Genome Wide Association Study Data in Obstructive Sleep Apnea. | Yu Liu, Sanjay R. Patel, Rod K. Nibbe, Sean Maxwell, Salim A. Chowdhury, Mehmet Koyutrk, Xiaofeng Zhu, Emma Larkin, Sarah Buxbaum, Naresh Punjabi, Sina Gharib, Susan Redline, Mark R. Chance |
| 2008 | PRICAI | NIIA: Nonparametric Iterative Imputation Algorithm. | Shichao Zhang, Zhi Jin, Xiaofeng Zhu |
| 2007 | AAAI | Measuring the Uncertainty of Differences for Contrasting Groups. | Jilian Zhang, Shichao Zhang, Xiaofeng Zhu, Xindong Wu, Chengqi Zhang |
| 2007 | AAAI | Cost-Sensitive Imputing Missing Values with Ordering. | Xiaofeng Zhu, Shichao Zhang, Jilian Zhang, Chengqi Zhang |
| 2007 | KSEM | Cost-Time Sensitive Decision Tree with Missing Values. | Shichao Zhang, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang |
| 2007 | PAKDD | GBKII: An Imputation Method for Missing Values. | Chengqi Zhang, Xiaofeng Zhu, Jilian Zhang, Yongsong Qin, Shichao Zhang |
| 2006 | DaWaK | Difference Detection Between Two Contrast Sets. | Huijing Huang, Yongsong Qin, Xiaofeng Zhu, Jilian Zhang, Shichao Zhang |
| 2006 | ICDM | Identifying Follow-Correlation Itemset-Pairs. | Shichao Zhang, Jilian Zhang, Xiaofeng Zhu, Zifang Huang |
| 2006 | PRICAI | Optimized Parameters for Missing Data Imputation. | Shichao Zhang, Yongsong Qin, Xiaofeng Zhu, Jilian Zhang, Chengqi Zhang |
| 2004 | PSB | Haplotype Block Definition and Its Application. | Xiaofeng Zhu, Shuanglin Zhang, Donghai Kan, Richard S. Cooper |