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).