l_{1,\infty}-Mixed Norm Promoted Row Sparsity for Fast Online CUR Decomposition Learning in Varying Feature Spaces [PDF]
Zhong Chen*, Yi He, Di Wu, Wenbin Zhang, and Zhiqiang Deng
Proceedings of the 2025 SIAM International Conference on Data Mining (SDM'25), Alexandria, Virginia, 2025. (Regular Paper, Acceptance Rate 61/228=26.7%)

l_{1,2}-Norm and CUR Decomposition based Sparse Active Online Learning for Data Streams with Streaming Features [PDF]
Zhong Chen*, Yi He, Di Wu, Liudong Zuo, Keren Li, Wenbin Zhang, and Zhiqiang Deng
IEEE International Conference on Big Data (IEEE BigData'24), pp. 374-383, 2024. (Regular Paper, Acceptance Rate 124/660=18.8%)

Adaptive Sparse Online Learning through Asymmetric Truncated Gradient [PDF]
Zhong Chen*
The 10th IEEE International Conference on Big Data Computing Service and Machine Learning Applications (IEEE BigDataService 2024), pp. 44-51, 2024. (Regular Paper, Accepted)

l_{1,2}-Norm and CUR Matrix Decomposition based Sparse Active Online Learning for Data Streams with Streaming Features [PDF]
Zhong Chen*
The 1st International Conference on Artificial Intelligence & Machine Learning (AIM'24), San Francisco, CA, 2024. (Oral Presentation)

Robust Sparse Online Learning through Adversarial Sparsity Constraints [PDF]
Zhong Chen*
The 9th IEEE International Conference on Smart Cloud (IEEE SmartCloud 2024), pp. 42-47, 2024. (Regular Paper, Accepted)

Robust Sparse Online Learning for Data Streams with Streaming Features [PDF]
Zhong Chen*, Yi He, Di Wu, Huixin Zhan, Victor Sheng, and Kun Zhang
Proceedings of the 2024 SIAM International Conference on Data Mining (SDM'24), Houston, United States, pp. 181-189, 2024. (Regular Paper, Acceptance Rate 98/416=23.6%)

Cost-sensitive Sparse Group Online Learning for Imbalanced Data Streams [PDF]
Zhong Chen*, Victor Sheng, Andrea Edwards, and Kun Zhang
Machine Learning (MLJ), 113, pp. 4407-4444, 2024. (Accepted)

Online Semi-supervised Learning with Mix-Typed Streaming Features [PDF]
Di Wu, Shengda Zhuo, Yu Wang, Zhong Chen#, and Yi He
The 37th AAAI Conference on Artificial Intelligence (AAAI'23), Washington DC, United States, 2023. (Regular Paper, Acceptance Rate 1721/8777=19.6%)

An Effective Cost-sensitive Sparse Online Learning Framework for Imbalanced Streaming Data Classification and Its Application to Online Anomaly Detection [PDF]
Zhong Chen*, Victor Sheng, Andrea Edwards, and Kun Zhang
Knowledge and Information Systems (KAIS), 65(1), pp. 59–87, 2023. 

Proximal Cost-sensitive Sparse Group Online Learning [PDF]
Zhong Chen*, Huixin Zhan, Victor Sheng, Andrea Edwards, and Kun Zhang
The 2022 IEEE International Conference on Big Data (IEEE Big Data'22), pp. 495-504, Osaka, Japan, 2022. (Regular Paper, Acceptance Rate 122/633=19.3%)

Projection Dual Averaging based Second-order Online Learning [PDF]
Zhong Chen*, Huixin Zhan, Victor Sheng, Andrea Edwards, and Kun Zhang
The 22nd IEEE International Conference on Data Mining (ICDM'22), pp. 51-60, Orlando, Florida, United States, 2022. (Regular Paper, Acceptance Rate 85/885=9.6%)

CSRDA: Cost-sensitive Regularized Dual Averaging for Handling Imbalanced and High-dimensional Streaming Data [PDF]
Zhong Chen*, Zhide Fang, Victor Sheng, Andrea Edwards, and Kun Zhang
The 12th IEEE International Conference on Big Knowledge (ICBK'21), pp. 164-173, Auckland, New Zealand, 2021. (Regular Paper)

Adaptive Robust Local Online Density Estimation for Streaming Data [PDF]
Zhong Chen*, Zhide Fang, Victor S Sheng, Jiabin Zhao, Wei Fan, Andrea Edwards, and Kun Zhang
International Journal of Machine Learning and Cybernetics (JMLC), 12(6), pp. 1803-1824, 2021. 

Online Density Estimation over Streaming Data: A Local Adaptive Solution [PDF]
Zhong Chen*, Zhide Fang, Jiabin Zhao, Wei Fan, Andrea Edwards, and Kun Zhang
2018 IEEE International Conference on Big Data (BigData'18), pp. 201-210, Seattle, Washington, United States, 2018. (Regular Paper, Acceptance Rate 98/518=19.7%)

CSTG: An Effective Framework for Cost-sensitive Sparse Online Learning [PDF]
Zhong Chen*, Zhide Fang, Wei Fan, Andrea Edwards, and Kun Zhang
The 2017 SIAM International Conference on Data Mining (SDM'17), pp. 759-767, Houston, Texas, United States, 2017. (Regular Paper, Acceptance Rate 93/358=26.0%)

Driver Gene Detection through Bayesian Network Integration of Mutation and Expression Profiles [PDF]
Zhong Chen*, You Lu, Bo Cao, Wensheng Zhang, Andrea Edwards, and Kun Zhang
Bioinformatics, 38(10), pp. 2781–2790, 2022. 

Effective Cancer Subtype and Stage Prediction via Dropfeature-DNNs [PDF]
Zhong Chen*, Wensheng Zhang, Hongwen Deng, and Kun Zhang
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 19(1), pp. 107-120, 2022. 

Insufficient Lycopene Intake is Associated with High Risk of Prostate Cancer: A Cross-Sectional Study from the National Health and Nutrition Examination Survey (2003-2010) [PDF]
You Lu, Andrea Edwards, Zhong Chen#, Tung-sung Tseng, Mirandy Li, Gabrielle V Gonzalez, and Kun Zhang
Frontiers in Public Health (FPH), p.792572, 2021. 

A Deep Imputation and Inference Framework for Estimating Personalized and Race-specific Causal Effects of Genomic Alterations on PSA [PDF]
Zhong Chen*, Bo Cao, Andrea Edwards, Hongwen Deng, and Kun Zhang
Journal of Bioinformatics and Computational Biology (JBCB), 19(4), p.2150016, 2021. 

Fusion Lasso and Its Applications to Cancer Subtype and Stage Prediction [PDF]
Zhong Chen*, Andrea Edwards, and Kun Zhang
The 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB'20), Virtual, pp. 1-8, 2020. (Short Paper, Acceptance Rate 17/130=13.1%)

Inferring Personalized and Race-specific Causal Effects of Genomic Aberrations on Gleason Scores: A Deep Latent Variable Model [PDF]
Zhong Chen*, Andrea Edwards, Chindo Hicks, and Kun Zhang
Frontiers in Oncology (FIO), 10, pp. 272, 2020. 

An Oversampling-enhanced Multi-class Imbalanced Classification Framework for Patient Health Status Prediction Using Patient-reported Outcomes [PDF]
Yang Yan, Zhong Chen#, Cai Xu, Xinglei Shen, Jay Shiao, John Einck, Ronald C Chen, and Hao Gao
arXiv preprint arXiv:2411.10819, 2024. 

Accounting for Cancer Patients with Severe Outcomes: An Anomaly Detection Perspective [PDF]
Yang Yan, Christopher Lominska, Gregory N Gan, Hao Gao, and Zhong Chen#
IEEE International Conference on Big Data (IEEE BigData'24), pp. 8225-8227, 2024. (Accepted)

Accurate proton-photon patient selection via dose and NTCP prediction for head-and-neck patients [PDF]
Jiaxin Li, Zhong Chen#, Fazal Khan, Yanan Zhu, Gregory N Gan, Christoper Lominska, Qiang Li, Weiqiang Chen, Hao Gao, and Yuting Lin
International Journal of Particle Therapy (IJPT), 12, p.100145, 2024. 

Metric-Agnostic Continual Learning for Sustainable Group Fairness [PDF]
Heng Lian, Chen Zhao, Zhong Chen#, Xingquan Zhu, My T. Thai, and Yi He
The 39th AAAI Conference on Artificial Intelligence (AAAI'25), Philadelphia, PA, 2025. (Regular Paper, Acceptance Rate 3,032/12,957=23.4%)

Advancing Graph Counterfactual Fairness through Fair Disentangled Representation [PDF]
Zichong Wang, Zhibo Chu, Ronald Blanco, Zhong Chen#, Shu-Ching Chen, and Wenbin Zhang
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'24), pp. 40-58, 2024. (Regular Paper, Acceptance Rate 198/826=24.0%)

Individual Fairness with Group Awareness under Uncertainty [PDF]
Zichong Wang, Xiaoyong Yuan, Zhong Chen#, Yanzhao Wu, Xin Yao, and Wenbin Zhang
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'24), pp. 89-106, 2024. (Regular Paper, Acceptance Rate 198/826=24.0%)

Distributed Collaborative Learning with Representative Knowledge Sharing [PDF]
Joseph Casey, Qianjiao Chen, Mengchen Fan, Baocheng Geng, Roman Shterenberg, Zhong Chen#, and Keren Li
Mathematics, 13(6): 1004, 2025. 

Measuring Heterogeneity in Machine Learning with Distributed Energy Distance [PDF]
Mengchen Fan, Baocheng Geng, Roman Shterenberg, Joseph A. Casey, Zhong Chen#, and Keren Li
arXiv preprint arXiv: 2501.16174, 2025. 

MCCA-MOT: Multimodal collaboration-guided cascade association network for 3D multi-object tracking [PDF]
Hui Li, Hengyuan Liu, Zhenzhen Du, Zhong Chen#, and Ye Tao
IEEE Transactions on Intelligent Transportation Systems (T-ITS), 26(1), pp. 974-989, 2025. 

Balancing Cost and Completion Time Through Variable Paths with Variable Bandwidth in HPNs [PDF]
Liudong Zuo, Zhong Chen#, and Lai Pan
International Conference on Computing, Networking and Communications (ICNC'25), Honolulu, Hawaii, 2025. (Accepted)

A Dynamic 3D Multi-Object Tracking Method Based on Spatiotemporal Features [PDF]
Hui Li, Haoran Yang, Xiaoxue Ai, Zhong Chen#, and Yanli Wu
IEEE Transactions on Intelligent Vehicles (T-IV), 2024. 

Optimal Scheduling Algorithms for Cost-Effective Bandwidth Reservation in HPNs [PDF]
Liudong Zuo, Lai Pan, and Zhong Chen#
IEEE International Conference on Big Data (IEEE BigData'24), pp. 483-488, 2024. (Short Paper, Acceptance Rate 130/660=19.7%)

An end-to-end knowledge graph fused graph neural network for accurate protein-protein interactions prediction [PDF]
Jie Yang, Yapeng Li, Guoyin Wang, Zhong Chen#, and Di Wu
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 21(6), pp. 2518-2530, 2024. 

MKG-FENN: A Multimodal Knowledge Graph Fused End-to-End Neural Network for Accurate Drug–Drug Interaction Prediction [PDF]
Di Wu, Wu Sun, Yi He, Zhong Chen#, and Xin Luo
The 38th AAAI Conference on Artificial Intelligence (AAAI'24), Vancouver, Canada, 38(9), pp. 10216-10224, 2024. (Regular Paper, Acceptance Rate 2342/9862=23.75%)

Defense Against Adversarial Attacks for Neural Representations of Text [PDF]
Huixin Zhan, Kun Zhang, Zhong Chen#, and Victor Sheng
Hawaii International Conference on System Sciences 2024 (HICSS'24), pp. 7592-7601, 2024. (Accepted)

Simplex2vec Backward: From Vectors Back to Simplicial Complex [PDF]
Huixin Zhan, Kun Zhang, Zhong Chen#, and Victor Sheng
The 32nd ACM International Conference on Information and Knowledge Management (CIKM'23), Birmingham, United Kingdom, 2023. (Short Paper, Acceptance Rate 152/554=27.4%)

Defending the Graph Reconstruction Attacks for Simplicial Neural Networks [PDF]
Huixin Zhan, Kun Zhang, Zhong Chen#, and Victor Sheng
The 10th IEEE International Conference on Data Science and Advanced Analytics (DSAA'23), Thessaloniki, Greece, 2023. (Special Session Paper, Acceptance Rate 12/35=34.3%)

MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data [PDF]
Cheng Liang, Di Wu, Yi He, Zhong Chen#, Teng Huang, and Xin Luo
The 22ed European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'23), Turin, Italy, 2023. (Regular Paper, Acceptance Rate 199/830=24.0%)

Learning Discriminative Subregions and Pattern Orders for Facial Gender Classification [PDF]
Zhong Chen*, Andrea Edwards, Yongsheng Gao, and Kun Zhang
Image and Vision Computing (IVC), 89, pp. 144-157, 2019. 

Construction Method of Concept Lattice Based on Improved Variable Precision Rough Set [PDF]
Ruiling Zhang, Shengwu Xiong, and Zhong Chen#
Neurocomputing (NC), 188, pp. 326-338, 2016. 

Topologically Ordered Feature Extraction Based on Sparse Group Restricted Boltzmann Machines [PDF]
Zhong Chen*, Shengwu Xiong, Zhixiang Fang, Ruiling Zhang, Xiangzhen Kong, and Yi Rong
Mathematical Problems in Engineering (MPIE), 2015. 

A Kernel Support Vector Machine-based Feature Selection Approach for Recognizing Flying Apsaras’ Streamers in the Dunhuang Grotto Murals, China [PDF]
Zhong Chen*, Shengwu Xiong, Zhixiang Fang, Qingquan Li, Baolin Wang, and Qin Zou
Pattern Recognition Letters (PRL), 49, pp. 107-113, 2014.