| 2025 | AAAI | Metric-Agnostic Continual Learning for Sustainable Group Fairness. | Heng Lian, Chen Zhao, Zhong Chen, Xingquan Zhu, My T. Thai, Yi He |
| 2025 | CIKM | OASIS: Harnessing Diffusion Adversarial Network for Ocean Salinity Imputation using Sparse Drifter Trajectories. | Bo Li, Yingqi Feng, Ming Jin, Xin Zheng, Yufei Tang, Laurent M. Chrubin, Can Wang, Alan Wee-Chung Liew, Qinghua Lu, Jingwei Yao, Hong Zhang, Shirui Pan, Xingquan Zhu |
| 2025 | ICDM | LHGEL: Large Heterogeneous Graph Ensemble Learning using Batch View Aggregation. | Jiajun Shen, Yufei Jin, Yi He, Xingquan Zhu |
| 2025 | ICML | Topology-aware Neural Flux Prediction Guided by Physics. | Haoyang Jiang, Jindong Wang, Xingquan Zhu, Yi He |
| 2025 | ICMLA | Survival Analysis for Employee Retention Prediction in Retail and Trade Sector Organizations. | Ariel Gonzalez Batista, Xingquan Zhu |
| 2025 | ICMLA | EDLAD: Ensemble Deep Learning for Alzheimer's Disease Detection using Brain EEG Signals. | An T. T. Phan, Xingquan Zhu |
| 2025 | IJCAI | HGEN: Heterogeneous Graph Ensemble Networks. | Jiajun Shen, Yufei Jin, Kaibu Feng, Yi He, Xingquan Zhu |
| 2025 | IJCAI | Towards Fairness with Limited Demographics via Disentangled Learning. | Zichong Wang, Anqi Wu, Nuno Moniz, Shu Hu, Bart P. Knijnenburg, Xingquan Zhu, Wenbin Zhang |
| 2024 | AAAI | GLDL: Graph Label Distribution Learning. | Yufei Jin, Richard Gao, Yi He, Xingquan Zhu |
| 2024 | ICDM | Graph Rhythm Network: Beyond Energy Modeling for Deep Graph Neural Networks. | Yufei Jin, Xingquan Zhu |
| 2024 | ICDM | Utilitarian Online Learning from Open-World Soft Sensing. | Heng Lian, Yu Huang, Xingquan Zhu, Yi He |
| 2024 | ICDM | Adaptable and Reliable Text Classification using Large Language Models. | Zhiqiang Wang, Yiran Pang, Yanbin Lin, Xingquan Zhu |
| 2023 | ICDM | On Computing Paradigms - Where Will Large Language Models Be Going. | Xindong Wu, Xingquan Zhu, Elena Baralis, Ruqian Lu, Vipin Kumar, Leszek Rutkowski, Jie Tang |
| 2023 | WSDM | SGCCL: Siamese Graph Contrastive Consensus Learning for Personalized Recommendation. | Boyu Li, Ting Guo, Xingquan Zhu, Qian Li, Yang Wang, Fang Chen |
| 2022 | CIKM | Local Contrastive Feature Learning for Tabular Data. | Zhabiz Gharibshah, Xingquan Zhu |
| 2022 | ICDM | Message from the ICDM 2022 Program Committee Chairs. | Xingquan Zhu, Sanjay Ranka |
| 2021 | IJCAI | GAEN: Graph Attention Evolving Networks. | Min Shi, Yu Huang, Xingquan Zhu, Yufei Tang, Yuan Zhuang, Jianxun Liu |
| 2021 | PAKDD | Weak Supervision Network Embedding for Constrained Graph Learning. | Ting Guo, Xingquan Zhu, Yang Wang, Fang Chen |
| 2020 | FlAIRS | MedFroDetect: Medicare Fraud Detection with Extremely Imbalanced Class Distributions. | Yuping Su, Xingquan Zhu, Bei Dong, Yumei Zhang, Xiaojun Wu |
| 2020 | FlAIRS | COPD Disease Classification Using Network Embedding with Synthetic Relationships. | Anak Wannaphaschaiyong, Xingquan Zhu |
| 2020 | ICDM | OpenWGL: Open-World Graph Learning. | Man Wu, Shirui Pan, Xingquan Zhu |
| 2020 | IJCAI | Multi-Class Imbalanced Graph Convolutional Network Learning. | Min Shi, Yufei Tang, Xingquan Zhu, David A. Wilson, Jianxun Liu |
| 2020 | WWW | Unsupervised Domain Adaptive Graph Convolutional Networks. | Man Wu, Shirui Pan, Chuan Zhou, Xiaojun Chang, Xingquan Zhu |
| 2019 | APWEB | Deep Learning for Online Display Advertising User Clicks and Interests Prediction. | Zhabiz Gharibshah, Xingquan Zhu, Arthur Hainline, Michael Conway |
| 2019 | CIKM | Long-short Distance Aggregation Networks for Positive Unlabeled Graph Learning. | Man Wu, Shirui Pan, Lan Du, Ivor W. Tsang, Xingquan Zhu, Bo Du |
| 2019 | ICDM | Domain-Adversarial Graph Neural Networks for Text Classification. | Man Wu, Shirui Pan, Xingquan Zhu, Chuan Zhou, Lei Pan |
| 2019 | ICDM | Relation Structure-Aware Heterogeneous Graph Neural Network. | Shichao Zhu, Chuan Zhou, Shirui Pan, Xingquan Zhu, Bin Wang |
| 2019 | IJCAI | Discriminative Sample Generation for Deep Imbalanced Learning. | Ting Guo, Xingquan Zhu, Yang Wang, Fang Chen |
| 2018 | ICDM | EDLT: Enabling Deep Learning for Generic Data Classification. | Huimei Han, Xingquan Zhu, Ying Li |
| 2018 | ICDM | Deep Structure Learning for Fraud Detection. | Haibo Wang, Chuan Zhou, Jia Wu, Weizhen Dang, Xingquan Zhu, Jilong Wang |
| 2018 | ICDM | SINE: Scalable Incomplete Network Embedding. | Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang |
| 2018 | ICMLA | Learning Convolutional Neural Networks from Ordered Features of Generic Data. | Eric Golinko, Thomas Sonderman, Xingquan Zhu |
| 2018 | IRI | Deep Transfer Learning for Traffic Sign Recognition. | Grant Rosario, Thomas Sonderman, Xingquan Zhu |
| 2018 | IRI | Tackling Class Imbalance in Cyber Security Datasets. | Charles Wheelus, Elias Bou-Harb, Xingquan Zhu |
| 2018 | PAKDD | MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding. | Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang |
| 2017 | CIKM | MGAE: Marginalized Graph Autoencoder for Graph Clustering. | Chun Wang, Shirui Pan, Guodong Long, Xingquan Zhu, Jing Jiang |
| 2017 | EDBT | Protecting Location Privacy in Spatial Crowdsourcing using Encrypted Data. | Bozhong Liu, Ling Chen, Xingquan Zhu, Ying Zhang, Chengqi Zhang, Weidong Qiu |
| 2017 | IJCAI | User Profile Preserving Social Network Embedding. | Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang |
| 2017 | IJCNN | Latent topic ensemble learning for hospital readmission cost reduction. | Christopher Baechle, Ankur Agarwal, Ravi S. Behara, Xingquan Zhu |
| 2017 | IJCNN | Localized sampling for hospital re-admission prediction with imbalanced sample distributions. | Xingquan Zhu, Jose Hurtado, Haicheng Tao |
| 2017 | IRI | GFEL: Generalized Feature Embedding Learning Using Weighted Instance Matching. | Eric Golinko, Xingquan Zhu |
| 2017 | IRI | ULTR-CTR: Fast Page Grouping Using URL Truncation for Real-Time Click Through Rate Estimation. | Hui Liu, Xingquan Zhu, Kristopher Kalish, Jeremy Kayne |
| 2016 | AAAI | Direct Discriminative Bag Mapping for Multi-Instance Learning. | Jia Wu, Shirui Pan, Peng Zhang, Xingquan Zhu |
| 2016 | CIKM | Collective Classification via Discriminative Matrix Factorization on Sparsely Labeled Networks. | Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang |
| 2016 | ICDE | TrGraph: Cross-network transfer learning via common signature subgraphs. | Meng Fang, Jie Yin, Xingquan Zhu, Chengqi Zhang |
| 2016 | ICDE | Joint structure feature exploration and regularization for multi-task graph classification. | Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Philip S. Yu |
| 2016 | ICDM | Homophily, Structure, and Content Augmented Network Representation Learning. | Daokun Zhang, Jie Yin, Xingquan Zhu, Chengqi Zhang |
| 2016 | IJCAI | Tri-Party Deep Network Representation. | Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, Yang Wang |
| 2016 | IJCAI | Bernoulli Random Forests: Closing the Gap between Theoretical Consistency and Empirical Soundness. | Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu, Xingquan Zhu |
| 2016 | IJCNN | Co-clustering enterprise social networks. | Ruiqi Hu, Shirui Pan, Guodong Long, Xingquan Zhu, Jing Jiang, Chengqi Zhang |
| 2015 | IJCAI | Multi-Graph-View Learning for Complicated Object Classification. | Jia Wu, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang |
| 2015 | IRI | Gender Prediction in Random Chat Networks Using Topological Network Structures and Masked Content. | Michael Crawford, Xingquan Zhu |
| 2015 | IRI | Topic Discovery and Future Trend Prediction Using Association Analysis and Ensemble Forecasting. | Jose Hurtado, Shihong Huang, Xingquan Zhu |
| 2015 | WISE | Social Network Privacy: Issues and Measurement. | Isabel Casas, Jose Hurtado, Xingquan Zhu |
| 2014 | CIKM | Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning. | Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang |
| 2014 | ICDM | SNOC: Streaming Network Node Classification. | Ting Guo, Xingquan Zhu, Jian Pei, Chengqi Zhang |
| 2014 | ICDM | Multi-graph-view Learning for Graph Classification. | Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, Chengqi Zhang |
| 2014 | ICDM | Document-Specific Keyphrase Extraction Using Sequential Patterns with Wildcards. | Fei Xie, Xindong Wu, Xingquan Zhu |
| 2014 | IJCNN | Attribute weighting: How and when does it work for Bayesian Network Classification. | Jia Wu, Zhihua Cai, Shirui Pan, Xingquan Zhu, Chengqi Zhang |
| 2014 | IJCNN | Dual instance and attribute weighting for Naive Bayes classification. | Jia Wu, Shirui Pan, Zhihua Cai, Xingquan Zhu, Chengqi Zhang |
| 2014 | IRI | Who wrote this paper? Learning for authorship de-identification using stylometric featuress. | Jose Hurtado, Napat Taweewitchakreeya, Xingquan Zhu |
| 2014 | IRI | iSRD: Spam review detection with imbalanced data distributions. | Hamzah Al Najada, Xingquan Zhu |
| 2014 | PAKDD | Super-Graph Classification. | Ting Guo, Xingquan Zhu |
| 2014 | PAKDD | Multi-Instance Learning from Positive and Unlabeled Bags. | Jia Wu, Xingquan Zhu, Chengqi Zhang, Zhihua Cai |
| 2014 | SDM | Context-Preserving Hashing for Fast Text Classification. | Lianhua Chi, Bin Li, Xingquan Zhu |
| 2014 | SDM | Multi-Graph Learning with Positive and Unlabeled Bags. | Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Chengqi Zhang, Zhihua Cai |
| 2013 | CIKM | Active exploration: simultaneous sampling and labeling for large graphs. | Meng Fang, Jie Yin, Xingquan Zhu |
| 2013 | CIKM | Graph hashing and factorization for fast graph stream classification. | Ting Guo, Lianhua Chi, Xingquan Zhu |
| 2013 | CIKM | Understanding the roles of sub-graph features for graph classification: an empirical study perspective. | Ting Guo, Xingquan Zhu |
| 2013 | ICDE | Graph stream classification using labeled and unlabeled graphs. | Shirui Pan, Xingquan Zhu, Chengqi Zhang, Philip S. Yu |
| 2013 | ICDM | Transfer Learning across Networks for Collective Classification. | Meng Fang, Jie Yin, Xingquan Zhu |
| 2013 | ICDM | Multi-instance Multi-graph Dual Embedding Learning. | Jia Wu, Xingquan Zhu, Chengqi Zhang, Zhihua Cai |
| 2013 | ICDM | UBLF: An Upper Bound Based Approach to Discover Influential Nodes in Social Networks. | Chuan Zhou, Peng Zhang, Jing Guo, Xingquan Zhu, Li Guo |
| 2013 | ICMLA | A Classifier Ensembling Approach for Imbalanced Social Link Prediction. | Jose Hurtado, Napat Taweewitchakreeya, Xue Kong, Xingquan Zhu |
| 2013 | IJCAI | Graph Classification with Imbalanced Class Distributions and Noise. | Shirui Pan, Xingquan Zhu |
| 2013 | IJCNN | Self-adaptive probability estimation for Naive Bayes classification. | Jia Wu, Zhihua Cai, Xingquan Zhu |
| 2013 | IJCNN | Artificial immune system for attribute weighted Naive Bayes classification. | Jia Wu, Zhihua Cai, Sanyou Zeng, Xingquan Zhu |
| 2013 | ICTAI | An Empirical Study of Robustness of Network Centrality Scores in Various Networks and Conditions. | Matthew Herland, Pablo Pastran, Xingquan Zhu |
| 2013 | ICTAI | Machine Learning for Android Malware Detection Using Permission and API Calls. | Naser Peiravian, Xingquan Zhu |
| 2013 | PAKDD | Fast Graph Stream Classification Using Discriminative Clique Hashing. | Lianhua Chi, Bin Li, Xingquan Zhu |
| 2013 | SDM | Active Class Discovery and Learning for Networked Data. | Meng Fang, Jie Yin, Chengqi Zhang, Xingquan Zhu |
| 2012 | AAAI | Active Learning from Oracle with Knowledge Blind Spot. | Meng Fang, Xingquan Zhu, Chengqi Zhang |
| 2012 | CIKM | TCSST: transfer classification of short & sparse text using external data. | Guodong Long, Ling Chen, Xingquan Zhu, Chengqi Zhang |
| 2012 | CIKM | CGStream: continuous correlated graph query for data streams. | Shirui Pan, Xingquan Zhu |
| 2012 | CIKM | Continuous top-k query for graph streams. | Shirui Pan, Xingquan Zhu |
| 2012 | CIKM | Parallel proximal support vector machine for high-dimensional pattern classification. | Zhenfeng Zhu, Xingquan Zhu, Yangdong Ye, Yue-Fei Guo, Xiangyang Xue |
| 2012 | ICDM | Self-Taught Active Learning from Crowds. | Meng Fang, Xingquan Zhu, Bin Li, Wei Ding, Xindong Wu |
| 2012 | ICDM | Nested Subtree Hash Kernels for Large-Scale Graph Classification over Streams. | Bin Li, Xingquan Zhu, Lianhua Chi, Chengqi Zhang |
| 2012 | ICPR | I don't know the label: Active learning with blind knowledge. | Meng Fang, Xingquan Zhu |
| 2012 | ICPR | Top-k correlated subgraph query for data streams. | Shirui Pan, Xingquan Zhu, Meng Fang |
| 2011 | AAAI | Optimal Subset Selection for Active Learning. | Yifan Fu, Xingquan Zhu |
| 2011 | AAAI | Large Scale Diagnosis Using Associations between System Outputs and Components. | Ting Guo, Zhanshan Li, Ruizhi Guo, Xingquan Zhu |
| 2011 | AAAI | An Empirical Study of Bagging Predictors for Different Learning Algorithms. | Guohua Liang, Xingquan Zhu, Chengqi Zhang |
| 2011 | AAAI | Tracking User-Preference Varying Speed in Collaborative Filtering. | Ruijiang Li, Bin Li, Cheng Jin, Xiangyang Xue, Xingquan Zhu |
| 2011 | CIKM | Do they belong to the same class: active learning by querying pairwise label homogeneity. | Yifan Fu, Bin Li, Xingquan Zhu, Chengqi Zhang |
| 2011 | CIKM | Transfer active learning. | Zhenfeng Zhu, Xingquan Zhu, Yangdong Ye, Yue-Fei Guo, Xiangyang Xue |
| 2011 | ICDM | How Does Research Evolve? Pattern Mining for Research Meme Cycles. | Dan He, Xingquan Zhu, Douglas Stott Parker Jr. |
| 2011 | ICDM | Enabling Fast Lazy Learning for Data Streams. | Peng Zhang, Byron J. Gao, Xingquan Zhu, Li Guo |
| 2011 | IJCAI | Cross-Domain Collaborative Filtering over Time. | Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang, Xiangyang Xue, Xindong Wu |
| 2011 | KDD | Enabling fast prediction for ensemble models on data streams. | Peng Zhang, Jun Li, Peng Wang, Byron J. Gao, Xingquan Zhu, Li Guo |
| 2011 | PAKDD | Self-adjust Local Connectivity Analysis for Spectral Clustering. | Hui Wu, Guangzhi Qu, Xingquan Zhu |
| 2010 | CIKM | SKIF: a data imputation framework for concept drifting data streams. | Peng Zhang, Xingquan Zhu, Jianlong Tan, Li Guo |
| 2010 | CIKM | Transfer incremental learning for pattern classification. | Zhenfeng Zhu, Xingquan Zhu, Yue-Fei Guo, Xiangyang Xue |
| 2010 | ICDM | Classifier and Cluster Ensembles for Mining Concept Drifting Data Streams. | Peng Zhang, Xingquan Zhu, Jianlong Tan, Li Guo |
| 2010 | KDD | Ensemble pruning via individual contribution ordering. | Zhenyu Lu, Xindong Wu, Xingquan Zhu, Josh C. Bongard |
| 2010 | PAKDD | Rule Synthesizing from Multiple Related Databases. | Dan He, Xindong Wu, Xingquan Zhu |
| 2009 | ICCS | Bias-Variance Analysis for Ensembling Regularized Multiple Criteria Linear Programming Models. | Peng Zhang, Xingquan Zhu, Yong Shi |
| 2009 | ICDM | Mining Data Streams with Labeled and Unlabeled Training Examples. | Peng Zhang, Xingquan Zhu, Li Guo |
| 2009 | ICDM | Vague One-Class Learning for Data Streams. | Xingquan Zhu, Xindong Wu, Chengqi Zhang |
| 2009 | IJCAI | Multiple Information Sources Cooperative Learning. | Xingquan Zhu, Ruoming Jin |
| 2009 | IRI | Feature Selection with biased Sample Distributions. | Abu H. M. Kamal, Xingquan Zhu, Abhijit S. Pandya, Sam Hsu |
| 2009 | ICTAI | Approximate Repeating Pattern Mining with Gap Requirements. | Dan He, Xingquan Zhu, Xindong Wu |
| 2009 | ICTAI | Error Detection and Uncertainty Modeling for Imprecise Data. | Dan He, Xingquan Zhu, Xindong Wu |
| 2009 | PAKDD | An Aggregate Ensemble for Mining Concept Drifting Data Streams with Noise. | Peng Zhang, Xingquan Zhu, Yong Shi, Xindong Wu |
| 2008 | FlAIRS | Contrast Pattern Mining with Gap Constraints for Peptide Folding Prediction. | Chinar C. Shah, Xingquan Zhu, Taghi M. Khoshgoftaar, Justin Beyer |
| 2008 | ICDM | Cleansing Noisy Data Streams. | Xingquan Zhu, Peng Zhang, Xindong Wu, Dan He, Chengqi Zhang, Yong Shi |
| 2008 | ICPR | VoB predictors: Voting on bagging classifications. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu |
| 2008 | ICPR | Bagging very weak learners with lazy local learning. | Xingquan Zhu, Chengyi Bao, Weidong Qiu |
| 2008 | IRI | An empirical study of supervised learning for biological sequence profiling and microarray expression data analysis. | Abu H. M. Kamal, Xingquan Zhu, Abhijit S. Pandya, Sam Hsu, Yong Shi |
| 2008 | IRI | VCI predictors: Voting on classifications from imputed learning sets. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu |
| 2008 | KDD | Categorizing and mining concept drifting data streams. | Peng Zhang, Xingquan Zhu, Yong Shi |
| 2008 | SAC | iVESTA: an interactive visualization and evaluation system for drive test data. | Yongsuk Lee, Xingquan Zhu, Abhijit S. Pandya, Sam Hsu |
| 2008 | SAC | Imputation-boosted collaborative filtering using machine learning classifiers. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu, Russell Greiner |
| 2007 | ICCS | Using WordNet to Disambiguate Word Senses for Text Classification. | Ying Liu, Peter Scheuermann, Xingsen Li, Xingquan Zhu |
| 2007 | ICCS | Pushing Frequency Constraint to Utility Mining Model. | Jing Wang, Ying Liu, Lin Zhou, Yong Shi, Xingquan Zhu |
| 2007 | ICDE | Discovering Relational Patterns across Multiple Databases. | Xingquan Zhu, Xindong Wu |
| 2007 | ICDM | Lazy Bagging for Classifying Imbalanced Data. | Xingquan Zhu |
| 2007 | ICDM | Active Learning from Data Streams. | Xingquan Zhu, Peng Zhang, Xiaodong Lin, Yong Shi |
| 2007 | IJCAI | Mining Complex Patterns across Sequences with Gap Requirements. | Xingquan Zhu, Xindong Wu |
| 2007 | IJCAI | An Empirical Study of the Noise Impact on Cost-Sensitive Learning. | Xingquan Zhu, Xindong Wu, Taghi M. Khoshgoftaar, Yong Shi |
| 2007 | IRI | Mining Frequent Patterns with Wildcards from Biological Sequences. | Yu He, Xindong Wu, Xingquan Zhu, Abdullah N. Arslan |
| 2007 | ISVC | Rule-Based Multiple Object Tracking for Traffic Surveillance Using Collaborative Background Extraction. | Xiaoyuan Su, Taghi M. Khoshgoftaar, Xingquan Zhu, Andres Folleco |
| 2006 | CVPR | Accelerated Kernel Feature Analysis. | Xianhua Jiang, Yuichi Motai, Robert R. Snapp, Xingquan Zhu |
| 2006 | GRC | Error awareness data mining. | Xingquan Zhu, Xindong Wu |
| 2006 | ICDM | Corrective Classification: Classifier Ensembling with Corrective and Diverse Base Learners. | Yan Zhang, Xingquan Zhu, Xindong Wu |
| 2006 | ICPR | Scalable Representative Instance Selection and Ranking. | Xingquan Zhu, Xindong Wu |
| 2005 | ICDM | Sequential Pattern Mining in Multiple Streams. | Gong Chen, Xindong Wu, Xingquan Zhu |
| 2005 | ICTAI | ACE: An Aggressive Classifier Ensemble with Error Detection, Correction, and Cleansing. | Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bond |
| 2005 | ISMIS | Scalable Inductive Learning on Partitioned Data. | Qijun Chen, Xindong Wu, Xingquan Zhu |
| 2005 | KDD | Combining proactive and reactive predictions for data streams. | Ying Yang, Xindong Wu, Xingquan Zhu |
| 2004 | AAAI | Error Detection and Impact-Sensitive Instance Ranking in Noisy Datasets. | Xingquan Zhu, Xindong Wu, Ying Yang |
| 2004 | ICDM | Cost-Guided Class Noise Handling for Effective Cost-Sensitive Learning. | Xingquan Zhu, Xindong Wu |
| 2004 | ICDM | Dynamic Classifier Selection for Effective Mining from Noisy Data Streams. | Xingquan Zhu, Xindong Wu, Ying Yang |
| 2004 | ICTAI | Data Acquisition with Active and Impact-Sensitive Instance Selection. | Xingquan Zhu, Xindong Wu |
| 2003 | ICDE | Medical Video Mining for Efficient Database Indexing, Management and Access. | Xingquan Zhu, Walid G. Aref, Jianping Fan, Ann Christine Catlin, Ahmed K. Elmagarmid |
| 2003 | ICML | Eliminating Class Noise in Large Datasets. | Xingquan Zhu, Xindong Wu, Qijun Chen |
| 2003 | IJCAI | Mining Video Associations for Efficient Database Management. | Xingquan Zhu, Xindong Wu |
| 2002 | ICDE | A Distributed Database Server for Continuous Media. | Walid G. Aref, Ann Christine Catlin, Ahmed K. Elmagarmid, Jianping Fan, J. Guo, Moustafa A. Hammad, Ihab F. Ilyas, Mirette S. Marzouk, Sunil Prabhakar, Abdelmounaam Rezgui, S. Teoh, Evimaria Terzi, Yi-Cheng Tu, Athena Vakali, Xingquan Zhu |
| 2002 | ICIP | Towards facial feature extraction and verification for omni-face detection in video/images. | Xingquan Zhu, Jianping Fan, Ahmed K. Elmagarmid |