Publications

First  Author;  Collaborative  Author)



    2025
  1. 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%)


  2. 2024
  3. 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%)

  4. 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)

  5. 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)

  6. 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)

  7. 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%)

  8. 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)


  9. 2023
  10. 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%)

  11. 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. 


  12. 2022
  13. 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%)

  14. 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%)


  15. 2021
  16. 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)

  17. 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. 


  18. 2018
  19. 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%)


  20. 2017
  21. 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%)



  22. 2022
  23. 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. 

  24. 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. 


  25. 2021
  26. 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. 

  27. 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. 


  28. 2020
  29. 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%)

  30. 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. 



  31. 2024
  32. 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. 

  33. 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)

  34. 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. 



  35. 2025
  36. 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%)


  37. 2024
  38. 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%)

  39. 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%)



  40. 2025
  41. 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. 

  42. 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. 

  43. 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)


  44. 2024
  45. 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. 

  46. 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%)

  47. 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. 

  48. 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%)

  49. 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)


  50. 2023
  51. 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%)

  52. 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%)

  53. 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%)


  54. 2019
  55. 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. 


  56. 2016
  57. 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. 


  58. 2015
  59. 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. 


  60. 2014
  61. 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.