Bojian Hou (侯博建)

Bojian Hou (侯博建)

Postdoctoral Researcher at Univerisity of Pennsylvania

Publications

Conference

  1. Zhuoping Zhou*, Davoud Ataee Tarzanagh*, Bojian Hou*, Boning Tong, Jia Xu, Yanbo Feng, Qi Long, Li Shen. Fair Canonical Correlation Analysis. In: Proceedings of the 37th Annual Conference on Neural Information Processing Systems (NeurIPS’23), New Orleans, LA, 2023, in press. (* means equal contribution or co-first authors) [PDF] [Code]
  2. Zhuoping Zhou, Boning Tong, Davoud Ataee Tarzanagh, Bojian Hou, Andrew J. Saykin, Qi Long, Li Shen. Multi-Group Tensor Canonical Correlation Analysis. In: Proceedings of the 14th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB, 2023), Houston, TX, 2023, in press. (This paper won the best paper award.) [PDF]
  3. Boning Tong, Zhuoping Zhou, Davoud Ataee Tarzanagh, Bojian Hou, Andrew J. Saykin, Jason Moore, Marylyn Ritchie, Li Shen. Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection. In: Proceedings of the 14th International Workshop on Machine Learning in Medical Imaging (MLMI’23), Vancouver, Canada, 2023, in press. [PDF]
  4. Davoud Ataee Tarzanagh*, Bojian Hou*, Boning Tong*, Qi Long, Li Shen. Fairness-Aware Class Imbalanced Learning on Multiple Subgroups. In: Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI’23), Pittsburgh, PA, 2023, in press. (* means equal contribution or co-first authors) [PDF] [Code]
  5. Bojian Hou, Hongming Li, Zhicheng Jiao, Zhen Zhou, Hao Zhang, Yong Fan. Deep Clustering Survival Machines with Interpretable Expert Distributions. In: Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI’23), Cartagena de Indias, Colombia, 2023, in press. [PDF] [Code]
  6. Mingquan Lin, Yuyun Xiao, Bojian Hou, Tingyi Wanyan, Mohit Manoj Sharma, Zhangyang Wang, Fei Wang, Sarah Van Tassel, Yifan Peng. Evaluate Underdiagnosis and Overdiagnosis Bias of Deep Learning Model on Primary Open-Angle Glaucoma Diagnosis in Under-Served Populations. In: Proceedings of the AMIA 2023 Informatics Summit, Seattle, WA, 2023, 370. [PDF]
  7. Heng Lian, John S. Atwood, Bo-Jian Hou, Jian Wu, Yi He. Online Deep Learning from Doubly-Streaming Data. In: Proceedings of the 30th ACM International Conference on Multimedia (ACMMM’22), Lisbon, Portugal, 2022, 3185-3194. [PDF]
  8. Bo-Jian Hou, Yu-Hu Yan, Peng Zhao and Zhi-Hua Zhou. Storage Fit Learning with Feature Evolvable Streams. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI’21), Virtual Conference, 2021, 35(9), 7729-7736. [ArXiv] [Code]
  9. Yi He, Jiaxian Dong, Bo-Jian Hou, Yu Wang, and Fei Wang. Online Learning in Variable Feature Spaces with Mixed Data. In: Proceedings of the 21st IEEE International Conference on Data Mining (ICDM’21), Auckland, New Zealand, 2021, in press. [PDF]
  10. Bo-Jian Hou and Yuan Jiang. Learning Interpretability from RNN with Feature Evolving. In: CCF Conference on Artificial Intelligence (CCFAI’19), Xuzhou, China, 2019. (This paper won the CCFAI Outstanding Student Paper Award.)
  11. Bo-Jian Hou, Lijun Zhang, and Zhi-Hua Zhou. Learning with Feature Evolvable Streams. In: Advances in Neural Information Processing Systems 30 (NIPS’17), Long Beach, CA, 2017, 30: 1417-1427. [PDF] [Poster] [Code]
  12. Bo-Jian Hou, Lijun Zhang, and Zhi-Hua Zhou. Storage Fit Learning with Unlabeled Data. In: Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI’17), Melbourne, Australia, 2017, 1844-1850. [PDF] [Poster] [Code] [Page]

Journal

  1. Heng Lian, Di Wu, Bo-Jian Hou, Jian Wu, and Yi He. Online Learning from Evolving Feature Spaces with Deep Variational Models. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023, in press. [PDF]
  2. Mingquan Lin, Bojian Hou, Swati Mishra, Tianyuan Yao, Yuankai Huo, Qian Yang, Fei Wang, George Shih, Yifan Peng. Enhancing thoracic disease detection using chest X-rays from PubMed Central Open Access. Computers in Biology and Medicine, 2023: 106962. [PDF]
  3. Mingquan Lin, Bojian Hou, Lei Liu, Mae Gordon, Michael Kass, Fei Wang, Sarah H. Van Tassel, Yifan Peng. Automated diagnosing primary open-angle glaucoma from fundus image by simulating human’s grading with deep learning. Scientific Report, 2022, 12(1): 1-10. [PDF]
  4. Bo-Jian Hou, Lijun Zhang, and Zhi-Hua Zhou. Prediction with Unpredictable Feature Evolution. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021, in press. [ArXiv] [Code]
  5. Bo-Jian Hou and Zhi-Hua Zhou. Learning with Interpretable Structure from Gated RNN. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020, 31(7): 2267-2279. [PDF] [Code]
  6. Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou. Learning with Feature Evolvable Streams. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019, 33(6): 2602-2615. [PDF]
  7. Jie Ren, Bojian Hou, and Yuan Jiang. Deep Forest for Multiple Instance Learning. Journal of Computer Research and Development, 2019, 56(8): 1670-1676. [PDF]

Manuscript

  1. Bojian Hou, Hao Zhang, Gur Ladizhinsky, Ali Kayyal, Stephen Yang, Volodymyr Kuleshov, Fei Wang and Qian Yang. Clinical Evidence Engine: Proof-of-Concept For a Clinical-Domain-Agnostic Decision Support Infrastructure. [Arxiv]
  2. Jing-Xiao Liao, Bo-Jian Hou, Hang-Cheng Dong, Hao Zhang, Jianwei Ma, Jinwei Sun, Shiping Zhang, Feng-Lei Fan. Heterogeneous Autoencoder Empowered by Quadratic Neurons. [Arxiv]
  3. Dayang Wang, Feng-Lei Fan, Bo-Jian Hou, Hao Zhang, Rongjie Lai, Hengyong Yu, Fei Wang. Manifoldron: Direct Space Partition via Manifold Discovery. [Arxiv]