Junyu Luo

Junyu Luo

Publications

You can also find my articles on my Google Scholar profile.

  1. Luo, J., Wang, J., & Lin, C.-Y. (2021). Hybrid cascade point search network for high precision bar chart component detection. In 2020 25th International Conference on Pattern Recognition (ICPR) (pp. 6688-6695). IEEE.

  2. Ye, M., Luo, J., Xiao, C., & Ma, F. (2020). Lsan: Modeling long-term dependencies and short-term correlations with hierarchical attention for risk prediction. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management (pp. 1753-1762).

  3. Luo, J., Xiao, C., Glass, L., Sun, J., & Ma, F. (2021). Fusion: towards automated ICD coding via feature compression. In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (pp. 2096-2101).

  4. Luo, J., Lin, J., Lin, C., Xiao, C., Gui, X., & Ma, F. (2022). Benchmarking automated clinical language simplification: Dataset, algorithm, and evaluation. In Proceedings of the 29th International Conference on Computational Linguistics (pp. 3550-3562).

  5. Luo, J., Li, Z., Wang, J., & Lin, C.-Y. (2021). Chartocr: Data extraction from charts images via a deep hybrid framework. In Proceedings of the IEEE/CVF winter conference on applications of computer vision (pp. 1917-1925).

  6. Ye, M., Cui, S., Wang, Y., Luo, J., Xiao, C., & Ma, F. (2021). Medretriever: Target-driven interpretable health risk prediction via retrieving unstructured medical text. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management (pp. 2414-2423).

  7. Luo, J., Ye, M., Xiao, C., & Ma, F. (2020). Hitanet: Hierarchical time-aware attention networks for risk prediction on electronic health records. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 647-656).

  8. Ye, M., Cui, S., Wang, Y., Luo, J., Xiao, C., & Ma, F. (2021). Medpath: Augmenting health risk prediction via medical knowledge paths. In Proceedings of the Web Conference 2021 (pp. 1397-1409).

  9. Huang, C., Zhu, J., Liang, Y., Yang, M., Fung, G. P. C., & Luo, J. (2019). An efficient automatic multiple objectives optimization feature selection strategy for internet text classification. International Journal of Machine Learning and Cybernetics, 10, 1151-1163.

  10. Ye, M., Luo, J., Zheng, G., Xiao, C., Xiao, H., Wang, T., & Ma, F. (2022). MedAttacker: Exploring black-box adversarial attacks on risk prediction models in healthcare. In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1777-1780). IEEE.

  11. Jiang, Z., Yu, S., Qu, Q., Yang, M., Luo, J., & Liu, J. (2018). Multi-task learning for author profiling with hierarchical features. In Companion Proceedings of the The Web Conference 2018 (pp. 55-56).

  12. Ma, F., Ye, M., Luo, J., Xiao, C., & Sun, J. (2021). Advances in mining heterogeneous healthcare data. In Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining (pp. 4050-4051).

  13. Long, Z., Che, L., Wang, Y., Ye, M., Luo, J., Wu, J., Xiao, H., & Ma, F. (2020). FedSiam: Towards adaptive federated semi-supervised learning. arXiv preprint arXiv:2012.03292.

  14. Luo, J., Yang, M., Shen, Y., Qu, Q., & Chai, H. (2019). Learning document embeddings with crossword prediction. In Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9993-9994.

  15. Long, Z., Che, L., Wang, Y., Ye, M., Luo, J., Wu, J., Xiao, H., & Ma, F. (2020). Fedsemi: An adaptive federated semi-supervised learning framework. arXiv preprint arXiv:2012.03292.

  16. Cui, S., Luo, J., Ye, M., Wang, J., Wang, T., & Ma, F. (2022). MedSkim: Denoised Health Risk Prediction via Skimming Medical Claims Data. In 2022 IEEE International Conference on Data Mining (ICDM) (pp. 81-90). IEEE.

  17. Luo, J., Shen, Y., Ao, X., Zhao, Z., & Yang, M. (2019). Cross-modal image-text retrieval with multitask learning. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (pp. 2309-2312).

  18. Luo, J., Zheng, Z., Ye, H., Ye, M., Wang, Y., You, Q., Xiao, C., & Ma, F. (2020). A benchmark dataset for understandable medical language translation. arXiv preprint arXiv:2012.02420.

  19. Luo, J., Xu, Y., Tang, C., & Lv, J. (2017). Learning inverse mapping by autoencoder based generative adversarial nets. In Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part II 24 (pp. 207-216). Springer.