Journal Publications

See my Google Scholar for most recent publications.

-2021-

    • 1. Liu, Y., Huang, A., Luo, Y., Huang, H., Liu, Y., Chen, Y., Feng, L., Chen, T., Yu, H. & Yang, Q. Federated learning-powered visual object detection for safety monitoring. AI Magazine 42(2), AAAI Press (2021)

    • 2. Kairouz, P., McMahan, H. B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A. N., Bonawitz, K., Charles, Z., Cormode, G., Cummings, R., D'Oliveira, R. G. L., Rouayheb, S. E., Evans, D., Gardner, J., Garrett, Z., Gascón, A., Ghazi, B., Gibbons, P. B., Gruteser, M., Harchaoui, Z., He, C., He, L., Huo, Z., Hutchinson, B., Hsu, J., Jaggi, M., Javidi, T., Joshi, G., Khodak, M., Konečný, J., Korolova, A., Koushanfar, F., Koyejo, S., Lepoint, T., Liu, Y., Mittal, P., Mohri, M., Nock, R., Özgür, A., Pagh, R., Raykova, M., Qi, H., Ramage, D., Raskar, R., Song, D., Song, W., Stich, S. U., Sun, Z., Suresh, A. T., Tramèr, F., Vepakomma, P., Wang, J., Xiong, L., Xu, Z., Yang, Q., Yu, F. X., Yu, H. & Zhao, S. Advances and open problems in federated learning. Foundations and Trends in Machine Learning, Now Publishers (2021). (IF: 10.830)

    • 3. Q. Li, X. Wei, H. Lin, Y. Liu, T. Chen and X. Ma, "Inspecting the Running Process of Horizontal Federated Learning via Visual Analytics," in IEEE Transactions on Visualization and Computer Graphics, doi: 10.1109/TVCG.2021.3074010

-2020-

    • Yi, C., Xu, Y., Yu, H., Yan, Y. & Y. Liu, Multi-component transfer metric learning for handling unrelated source domain samples. Knowledge-Based Systems, Elsevier (2020)

    • Y. Liu, Y. Kang et al, A Secure Federated Transfer Learning Framework, IEEE Intelligent Systems, 22 April 2020

    • Yu, H., Liu, Z., Liu, Y., Chen, T., Cong, M., Weng, X., Niyato, D. & Yang, Q. A sustainable incentive scheme for federated learning. IEEE Intelligent Systems 35(4), doi:10.1109/MIS.2020.2987774, IEEE (2020). (IF: 3.21)

    • Y. Cheng, Y.Liu, T. Chen. Q Yang, Federated learning for privacy-preserving AI, Communications of the ACM, Vol 63, No 12, 2020

- 2019 -

  • [AI Mag.] Y. Zheng, H. Yu, L. Cui, C. Miao, C. Leung, Y. Liu & Q. Yang. Addressing the challenges of government service provision with AI. AI Magazine, vol. 40, no. 4 (2019).

  • [IEEE Access] T. Wang, H. Yang, H. Yu, W. Zhou, Y. Liu & H. Song. A revenue-maximizing bidding strategy for demand-side platforms. IEEE Access, vol. 7, no. 1, pp. 68692–68706 (2019).

  • [ACM TIST] Q. Yang, Y. Liu, T. Chen & Y. Tong. Federated machine learning: Concept and applications. ACM Transactions on Intelligent Systems and Technology, vol. 10, no. 2, pp. 12:1–12:19 (2019).

  • P.Kairouz et al, Advances and Open Problems in Federated Learning, arXiv:1912.04977

  • [IEEE Transactions on Information Theory] X Niu, C. Xing, Y. Liu, L. Zhou, A Construction of Optimal Frequency Hopping Sequence Set via Combination of Multiplicative and Additive Groups of Finite Fields (2020)

- 2018 -

  • Q. Yang, Y. Liu, T. Chen & Y. Tong. 2018. Federated learning. Communications of the CCF, vol. 14, no. 688, pp. 49–55 (2018).

- 2014 -

  • [Nature] J. Palmer, F. Martelli, Y. Liu, R. Car, A.Z. Panagiotopoulos & P. G. Debenedetti. Metastable liquid-liquid transition in a molecular model of water. Nature, vol. 510, no. 7505, pp. 385–388 (2014).