- 2025 -
[IEEE TPAMI] Lee, W., Shi, Y., Yu, H., Cheng, L., Wang, X., Yan, Z. & Kong, F. HPformer: Low-parameter transformer with temporal dependency hierarchical propagation for health informatics. IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE (2025). (IF: 18.6)
[IEEE TKDE] Xiong, Y., Guo, Y., Pan, W., Yang, Q., Ming, Z., Zhang, X., Yu, H., Lin, T. & Tang, X. Camouflaged variational graph AutoEncoder against attribute inference attacks for cross-domain recommendation. IEEE Transactions on Knowledge and Data Engineering, IEEE (2025). (IF: 10.4)
[IEEE TKDE] Fan, T., Gu, H., Cao, X., Chan, C. S., Chen, Q., Chen, Y., Feng, Y., Gu, Y., Geng, J., Luo, B., Liu, S., Ong, W. K., Ren, C., Shao, J., Sun, C., Tang, X., Tae, H. X., Tong, Y., Wei, S., Wu, F., Xi, W., Xu, M., Yang, H., Yang, X., Yan, J., Yu, H., Yu, H., Zhang, T., Zhang, Y., Zhang, X., Zheng, Z., Fan, L. & Yang, Q. Ten challenging problems in federated foundation models. IEEE Transactions on Knowledge and Data Engineering, IEEE (2025). (IF: 10.4)
[IEEE JSAC] Ren, C., Tang, Y., Gao, Y., Sun, X., Skoglund, M., Dong, Z. Y., Yu, H. & Xiao, M. QFEVAL: Quantum federated ensembled variational adaptive learning for efficient dynamic security assessment in smart grids. IEEE Journal on Selected Areas in Communications 43(9), 3200–3213, IEEE (2025). (IF: 17.2)
[IEEE TNNLS] Ren, C., Yan, R., Zhu, H., Yu, H., Xu, M., Shen, Y., Xu, Y., Xiao, M., Dong, Z. Y., Skoglund, M., Niyato, D. & Kwek, L. C. Towards quantum federated learning. IEEE Transactions on Neural Networks and Learning Systems 36(9), 15580–15600, IEEE (2025). (IF: 8.9)
[IEEE TNNLS] Tang, X. & Yu, H. A cost-aware utility-maximizing bidding strategy for auction-based federated learning. IEEE Transactions on Neural Networks and Learning Systems 36(7), 12866–12879, IEEE (2025). (IF: 8.9)
[IEEE TNNLS] Liu, R., Xing, P., Deng, Z., Li, A., Guan, C. & Yu, H. Federated graph neural networks: Overview, techniques and challenges. IEEE Transactions on Neural Networks and Learning Systems 36(3), 4279–4295, IEEE (2025). (IF: 8.9)
[IEEE IoTJ] Wu, F., Tan, A. Z., Feng, S., Yu, H., Deng, T., Zhao, L., & Chen, Y. Federated class-incremental learning via weighted aggregation and distillation. IEEE Internet of Things Journal 12(12), 22489–22503, IEEE (2025). (IF: 8.9)
[IEEE IoTJ] Tang, X. & Yu, H. Fairness-aware reverse auction-based federated learning. IEEE Internet of Things Journal 12(7), 8862–8872, IEEE (2025). (IF: 8.9)
[IEEE TSC] Wu, X., Yu, H., Casale, G. & Gao, G. Towards cost-optimal policies for DAGs to utilize IaaS clouds with online learning. IEEE Transactions on Services Computing 18(4), 2439–2455, IEEE (2025). (IF: 5.8)
[EAAI] Ni, Y., Wu, Y., Li, J., Zeng, A., Yu, H. & Li, X. Dynamic masking-based feature interaction modeling for e-commerce click-through rate prediction. Engineering Applications of Artificial Intelligence 157, Elsevier (2025). (IF: 8.0)
[KIS] Wang, Y., Shi, Y., Wang, J. Yu, H., Wang, X., Yan, Z. & Kong, F. Multimodal contrastive learning with hyperbolic geometry for KG-based game recommendation. Knowledge and Information Systems, SpringerNature (2025). (IF: 3.1)
[IEEE TCSVT] Yi, C., Chen, H., Zhang, Y., Xu, Y., Zhou, Y., Cui, L. & Yu, H. FDAC: Federated domain adaptation via dual contrastive learning. IEEE Transactions on Circuits and Systems for Video Technology, IEEE (2025). (IF: 11.1)
[IEEE COMST] Ren, C., Yu, H., Peng, H., Tang, X., Zhao, B., Yi, L., Tan, A. Z., Gao, Y., Li, A., Li, X., Li, Z. & Yang, Q. Advances and open challenges in federated foundation models. IEEE Communications Surveys and Tutorials, IEEE (2025). (IF: 46.7)
[ACM TORS] Chen, Y., Huzhang, G., Yu, Q., Sun, H., Li, H.-Y., Li, J., Ni, Y., Zeng, A., Yu, H. & Zhou, Z. Learning personalizable clustered embedding for recommender systems. ACM Transactions on Recommender Systems 3(3), 40:1–40:38, ACM (2025).
[IEEE TNSE] Gao, Y., Ren, C., Yu, H., Xiao, M. & Skoglund, M. Fairness-aware multi-server federated learning task delegation over wireless networks. IEEE Transactions on Network Science and Engineering 12(2), 684–697, IEEE (2025). (IF: 7.9)
[ACM CSUR] Tang, X. & Yu, H. Towards trustworthy AI-empowered real-time bidding for online advertisement auctioning. ACM Computing Surveys 57(6), 150:1–150:36, ACM (2025). (IF: 28.0)
Zou, L., Ling, H., Lei, M., Fang, X., Cai, M. & Yu, H. Domain-independent gear pitting fault diagnosis using transformer encoder and LinSoftmax. Big Data Mining and Analytics 8(5), 1127–1147, Tsinghua University Press (2025). (IF: 6.2)
- 2024 -
[IEEE TMC] Li, A., Wang, G., Hu, M., Sun, J., Zhang, L., Tuan, L. A. & Yu, H. Joint client-and-sample selection for federated learning via bi-level optimization. IEEE Transactions on Mobile Computing 23(12), 15196–15209, IEEE (2024). (IF: 7.7)
[IEEE TBD] Wu, X. & Yu, H. MarS-FL: Enabling competitors to collaborate in federated learning. IEEE Transactions on Big Data 10(6), 801–811, IEEE (2024). (IF: 7.5)
[IEEE TBD] Chen, C., Lyu, L., Yu, H. & Chen, G. Practical attribute reconstruction attack against federated learning. IEEE Transactions on Big Data 10(6), 851–863, IEEE (2024). (IF: 7.5)
[IEEE TBD] Xing, P., Lu, S., Wu, L. & Yu, H. BiG-Fed: Bilevel optimization enhanced graph-aided federated learning. IEEE Transactions on Big Data 10(6), 903–914, IEEE (2024). (IF: 7.5)
[IEEE TBD] Shi, H., Xu, Y., Jiang, Y., Yu, H. & Cui, L. Efficient asynchronous multi-participant vertical federated learning. IEEE Transactions on Big Data 10(6), 940–952, IEEE (2024). (IF: 7.5)
[IEEE TBD] Tan, X., Ng, W. C., Lim, W. Y. B., Xiong, Z., Niyato, D. & Yu, H. Reputation-aware federated learning client selection based on stochastic integer programming. IEEE Transactions on Big Data 10(6), 953–964, IEEE (2024). (IF: 7.5)
[IEEE JSAC] Gao, Y., Ye, Z. & Yu, H. Cost-efficient computation offloading in SAGIN: A deep reinforcement learning and perception-aided approach. IEEE Journal on Selected Areas in Communications 42(12), 3462–3476, IEEE (2024). (IF: 13.8)
[IEEE JSTSP] Ren, C., Dong, Z., Yu, H., Xu, M., Xiong, Z. & Niyato, D. ESQFL: Digital twin-driven explainable and secured quantum federated learning for voltage stability assessment in smart grids. IEEE Journal of Selected Topics in Signal Processing 18(5), 946–978, IEEE (2024). (IF: 8.7)
Yao, R., Song, J., Li, Z., Yu, H., & Wang, Y. Smart meter data sharing for AI-enhanced energy systems: A review of relevant techniques and detailed case studies. IEEE Power and Energy Magazine 22(6), 42–53, IEEE (2024). (IF: 3.1)
[IEEE IoTJ] Chen, Y., Tan, A., Feng, S., Yu, H., Deng, T., Zhao, L. & Wu, F. General federated class-incremental learning with lightweight generative replay. IEEE Internet of Things Journal 11(20), 33927–33939, IEEE (2024). (IF: 8.2)
[IEEE TNNLS] Shi, Y., Yu, H. & Leung, C. Towards fairness-aware federated learning. IEEE Transactions on Neural Networks and Learning Systems 35(9), 11922–11938, IEEE (2024). (IF: 10.4)
[IEEE TITS] Liu, S., You, L., Zhu, R., Liu, B., Liu, R., Yu, H. & Yuen, C. AFM3D: An asynchronous federated meta-learning framework for driver distraction detection. IEEE Transactions on Intelligent Transportation Systems 25(8), 9659–9674, IEEE (2024). (IF: 7.9)
[IEEE TNNLS] Lyu, L., Yu, H., Ma, X., Chen, C., Sun, L., Zhao, J., Yang, Q. & Yu, P. S. Privacy and robustness in federated learning: Attacks and defenses. IEEE Transactions on Neural Networks and Learning Systems 35(7), 8726–8746, IEEE (2024). (IF: 10.4) [ESI Highly Cited Paper]
[PACMMOD] Li, A., Chen, Y., Zhang, J., Cheng, M., Huang, Y., Wu, Y., Luu, A. T. & Yu, H. Historical embedding-guided efficient large-scale federated graph learning. Proceedings of the ACM on Management of Data 2(3), 144:1–144:24, ACM (2024).
[IEEE TMC] Li, A., Huang, J., Jia, J., Peng, H., Zhang, L., Tuan, L. A., Yu, H. & Li, X.-Y. Efficient and privacy-preserving feature importance-based vertical federated learning. IEEE Transactions on Mobile Computing 23(6), 7238–7255, IEEE (2024). (IF: 7.9)
[IEEE IoTJ] Tang, X. & Yu, H. Efficient large-scale personalizable bidding for multi-agent auction-based federated learning. IEEE Internet of Things Journal 11(15), 26518–26530, IEEE (2024). (IF: 10.6)
[KBS] Yi, L., Shi, X., Wang, N., Wang, G., Liu, X., Shi, Z. & Yu, H. pFedKT: Personalized federated learning with dual knowledge transfer. Knowledge-Based Systems, Elsevier (2024). (IF: 8.8)
[NN] Li, Q., Feng, B., Tang, X., Yu, H. & Song, H. MuLAN: Multi-level attention-enhanced matching network for few-shot knowledge graph completion. Neural Networks 174, Elsevier (2024). (IF: 7.8)
[NN] Liu, R., Chen, Y., Li, A., Ding, Y., Yu, H. & Guan, G. Aggregating intrinsic information to enhance BCI performance through federated learning. Neural Networks 172, Elsevier (2024). (IF: 7.8)
[IEEE IoTJ] Ren, C., Yan, R., Xu, M., Yu, H., Xu, Y., Niyato, D. & Dong, Z. D. QFDSA: A quantum-secured federated learning system for smart grid dynamic security assessment. IEEE Internet of Things Journal 11(5), 8414–8426, IEEE (2024). (IF: 10.6)
[IEEE IoTJ] Ren, C., Yu, H., Yan, R., Li, Q., Xu, Y., Niyato, D. & Dong, Z. Y. SecFedSA: A secure differential privacy-based federated learning approach for smart cyber-physical grid stability assessment. IEEE Internet of Things Journal 11(4), 5578–5588, IEEE (2024). (IF: 10.6)
[IEEE IoTJ] Kaewpuang, R., Xu, M., Lim, W. Y. B., Niyato, D., Yu, H., Kang, J. & Shen, X. Cooperative resource management in quantum key distribution networks for semantic communication. IEEE Internet of Things Journal 11(3), 4454–4469, IEEE (2024). (IF: 10.6)
Feng, S., Yu, H. & Zhu, Y. MMVFL: A simple vertical federated learning framework for multi-class multi-participant scenarios. Sensors, MDPI (2024). (IF: 3.9)
- 2023 -
[IEEE TKDE] Zhang, Y., Wang, J., Chen, Y., Yu, H. & Qin, T. Adaptive memory networks with self-supervised learning for unsupervised anomaly detection. IEEE Transactions on Knowledge and Data Engineering 35(12), 12068–12080, IEEE (2023). (IF: 9.235)
[HSSCOMMS] Xu, H., Che, M., Say, S. Y. A., Yu, H., Zhou, Q., Shu, J., Sun, W. & Luo, X. Investigating customers' continuous trust towards mobile banking apps. Humanities and Social Sciences Communications, SpringerNature (2023). (IF: 3.5)
[IEEE TNNLS] Tan, A. Z., Yu, H., Cui, L. & Yang, Q. Towards personalized federated learning. IEEE Transactions on Neural Networks and Learning Systems 34(12), 9587–9603, IEEE (2023). (IF: 10.4) [ESI Highly Cited Paper]
[PACMMOD] Li, A., Cao, Y., Guo, J., Peng, H., Guo, Q. & Yu, H. FedCSS: Joint client-and-sample selection for hard sample-aware noise-robust federated learning. Proceedings of the ACM on Management of Data 1(3), 212:1–212:24, ACM (2023).
[IEEE JAS] Ren, C., Zou, C., Xiong, Z., Yu, H., Dong, Z. Y. & Niyato, D. Achieving 500x acceleration for adversarial robustness verification of tree-based smart grid dynamic security assessment. IEEE/CAA Journal of Automatica Sinica, IEEE (2023). (IF: 11.8)
[IEEE TVT] Guo, Y., Liu, W., Lu, Y., Nie, J., Lyu, L., Xiong, Z., Kang, J., Yu, H. & Niyato, D. Haze visibility enhancement for promoting traffic situational awareness in vision-enabled intelligent transportation. IEEE Transactions on Vehicular Technology 72(12), 15421–15435, IEEE (2023). (IF: 6.8)
[ACM CSUR] Liu, C. & Yu, H. AI-empowered persuasive video generation: A survey. ACM Computing Surveys 55(13), 285:1–285:31, ACM (2023). (IF: 23.8)
[CSEE JPES] Ren, C., Yu, H., Xu, Y. & Dong, Z. Y. Understanding discrepancy of power system dynamic security assessment with unknown faults: A reliable transfer learning-based method. CSEE Journal of Power and Energy Systems, CSEE (2023). (IF: 6.014)
[IEEE JETCAS] Ren, C., Wang, T., Yu, H., Xu, Y. & Dong, Z. Y. EFedDSA: An efficient differential privacy-based horizontal federated learning approach for smart grid dynamic security assessment. IEEE Journal on Emerging and Selected Topics in Circuits and Systems 13(3), 817–828, IEEE (2023). (IF: 5.877)
[KBS] Wang, J., Shi, Y., Yu, H., Yan, Z. , Li, H. & Chen, Z. A novel KG-based recommendation model via relation-aware attentional GCN. Knowledge-Based Systems 275, doi:10.1016/j.knosys.2023.110702, Elsevier (2023). (IF: 8.139)
[KBS] Bian, H., Tian, J., Yu, J. & Yu, H. Bayesian co-evolutionary optimization based entropy search for high-dimensional many-objective optimization. Knowledge-Based Systems 274, doi:10.1016/j.knosys.2023.110630, Elsevier (2023). (IF: 8.139)
[NN] Li, Q., Yao, J., Tang, X., Yu, H., Jiang, S., Yang, H. & Song, H. Capsule neural tensor networks with multi-aspect information for few-shot knowledge graph completion. Neural Networks 164, 323–334, Elsevier (2023). (IF: 9.657)
[IEEE TVT] Kaewpuang, R., Sawadsitang, S., Niyato, D. & Yu, H. Evolutionary carrier selection for shared truck delivery services. IEEE Transactions on Vehicular Technology 72(5), 6778–6782, IEEE (2023). (IF: 6.239)
[IEEE TNNLS] Yi, C., Chen, H., Xu, Y., Chen, H., Liu, Y., Tan, H., Yan, Y. & Yu, H. Multi-component adversarial domain adaptation: A general framework. IEEE Transactions on Neural Networks and Learning Systems 34(10), 6824–6838, IEEE (2023). (IF: 14.255)
[AI Mag.] Liu, Z., Chen, Y., Zhao, Y., Yu, H., Liu, Y., Bao, R., Jiang, J., Nie, Z., Xu, Q. & Yang, Q. CAreFL: Enhancing smart healthcare with contribution-aware federated learning. AI Magazine 44(1), 4–15, AAAI Press (2023). (IF: 2.524)
[AI Mag.] Guo, X., Wang, S., Zhao, H., Diao, S., Chen, J., Ding, Z., He, Z., Lu, J., Xiao, Y., Long, B., Yu, H. & Wu, L. Intelligent online selling point extraction and generation for e-commerce recommendation. AI Magazine 44(1), 16–29, AAAI Press (2023). (IF: 2.524) (Top Cited Article Award)
[AI Mag.] Zou, Y., Zhang, X., Zhou, J., Diao, S., Chen, J., Ding, Z., He, Z., He, X., Xiao, Y., Long, B., Ma, M., Xu, S., Yu, H. & Wu, L. Automatic product copywriting for e-commerce. AI Magazine 44(1), 41–53, AAAI Press (2023). (IF: 2.524)
Zhang, J. & Yu, H. EID: Facilitating explainable AI design discussions in team-based settings. International Journal of Crowd Science 7(2), 47–54, Tsinghua University Press (2023).
Zhang, J., Shu, Y. & Yu, H. Fairness in Design: A framework for facilitating ethical AI designs. International Journal of Crowd Science 7(1), 32–39, Tsinghua University Press (2023). (Excellent Paper Award)
[KBS] Wang, T., Yang, H., Liu, Y., Yu, H. & Song, H. A multimodal approach for improving market price estimation in online advertising. Knowledge-Based Systems 266, doi:10.1016/j.knosys.2023.110392, Elsevier (2023). (IF: 8.139)
[IEEE CM] Ngoenriang, N., Xu, M., Kang, J., Niyato, D., Yu, H., Shen, X. S. DQC2O: Distributed quantum computing for collaborative optimization in future networks. IEEE Communications Magazine, IEEE (2023). (IF: 9.03)
[ESA] Wang, J., Shi, Y., Yu, H., Zhang, K., Wang, X., Yan, Z. & Li, H. Temporal density-aware sequential recommendation networks with contrastive learning. Expert Systems with Applications 211, doi:10.1016/j.eswa.2022.118563, Elsevier (2023). (IF: 8.665)
[IEEE Network] Xie, Y.-A., Kang, J., Niyato, D., Van, N. T. T., Luong, N. C., Liu, Z. & Yu, H. Securing federated learning: A covert communication-based approach. IEEE Network 37(1), 118–124, IEEE (2023). (IF: 10.294)
[IEEE TKDE] Huzhang, G., Pang, Z.-J., Gao, Y., Liu, Y., Shen, W., Zhou, W.-J., Lin, Q., Da, Q., Zeng, A.-X., Yu, H., Yu, Y. & Zhou, Z.-H. AliExpress Learning-To-Rank: Maximizing online model performance without going online. IEEE Transactions on Knowledge and Data Engineering 35(2), 1214–1226, IEEE (2023). (IF: 9.235)
[IEEE TKDE] Yang, H., Wang, T., Tang, X., Yu, H., Liu, F. & Song, H. Dynamically optimizing display advertising profits under diverse budget settings. IEEE Transactions on Knowledge and Data Engineering 35(1), 362–376, IEEE (2023). (IF: 9.235)
- 2022 -
[KAIS] Cheng, L., Shi, Y., Li, L., Yu, H., Wang, X. & Yan, Z. KLECA: Knowledge-level-evolution and category-aware personalized knowledge recommendation. Knowledge and Information Systems 65(3), 1045–1065, Springer (2022). (IF: 2.531)
[KBS] Feng, S., Li, B., Yu, H., Liu, Y. & Yang, Q. Semi-supervised federated heterogeneous transfer learning. Knowledge-Based Systems 252, doi:10.1016/j.knosys.2022.109384, Elsevier (2022). (IF: 8.139)
[KBS] Yang, H., Jiang, S., Shi, Y., Li, Q., Tang, X., Yu, H. & Song, H. Kaplan-Meier Markov network: Learning the distribution of market price by censored data in online advertising. Knowledge-Based Systems 251, doi:10.1016/j.knosys.2022.109248, Elsevier (2022). (IF: 8.139)
[IEEE TII] Liu, R. W., Liang, M., Nie, J., Yuan, Y., Xiong, Z., Yu, H. & Guizani, N. STMGCN: Mobile edge computing-empowered vessel trajectory prediction using spatio-temporal multi-graph convolutional network. IEEE Transactions on Industrial Informatics 18(11), 7977–7987, IEEE (2022). (IF: 11.648) [ESI Highly Cited Paper]
[IEEE TGCN] Liu, R. W., Guo, Y., Nie, J., Hu, Q., Xiong, Z., Yu, H. & Guizani, M. Intelligent edge-enabled efficient multi-source data fusion for autonomous surface vehicles in maritime Internet of Things. IEEE Transactions on Green Communications and Networking 6(3), 1574–1587, IEEE (2022). (IF: 3.525)
[ACM TIST] Liu, Z., Chen, Y., Yu, H., Liu, Y. & Cui, L. GTG-Shapley: Efficient and accurate participant contribution evaluation in federated learning. ACM Transactions on Intelligent Systems and Technology 13(4), 60:1–60:21, ACM (2022). (IF: 10.489)
[ACM TIST] Guo, X., Yu, H., Li, B., Wang, H., Xing, P., Feng, S., Nie, Z. & Miao, C. Federated learning for personalized humor recognition. ACM Transactions on Intelligent Systems and Technology 13(4), 68:1–68:18, ACM (2022). (IF: 10.489) (PREMIA Certificate of Commendation)
[KBS] Hu, C., Chen, Y., Hu, L., Yu, H. & Lu, D. Disagreement-based class incremental random forest for sensor-based activity recognition. Knowledge-Based Systems 239, doi:10.1016/j.knosys.2021.108044, Elsevier (2022). (IF: 8.139)
- 2021 -
[AI Mag.] 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), 19–27, AAAI Press (2021). (IF: 2.524)
[AI Mag.] Zheng, Y., Yu, H., Shi, Y., Zhang, K., Zhen, S., Cui, L., Leung, C. & Miao, C. Optimizing smart grid operations from the demand side. AI Magazine 42(2), 28–37, AAAI Press (2021). (IF: 2.524)
[AI Mag.] Zeng, A., Yu, H., Da, Q., Zhan, Y., Yu, Y., Zhou, J. & Miao, C. Improving search engine efficiency through contextual factor selection. AI Magazine 42(2), 50–58, AAAI Press (2021). (IF: 2.524)
[KBS] Liu, Y., Zou, X. & Yu, H. 3R Model: A post-purchase context-aware reputation model to mitigate unfair ratings in e-commerce. Knowledge-Based Systems 231, doi:10.1016/j.knosys.2021.107441, Elsevier (2021). (IF: 8.139)
[IEEE TCSVT] Guo, S., Zhang, T., Xu, G., Yu, H., Xiang, T. & Liu, Y. Byzantine-resilient decentralized stochastic gradient descent. IEEE Transactions on Circuits and Systems for Video Technology 32(6), 4096–4106, IEEE (2021). (IF: 5.859)
[IEEE TCSVT] Guo, S., Zhang, T., Xu, G., Yu, H., Xiang, T. & Liu, Y. Topology-aware differential privacy for decentralized image classification. IEEE Transactions on Circuits and Systems for Video Technology 32(6), 4016–4027, IEEE (2021). (IF: 5.859)
[FnTML] 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 14(1-2), 1–210, Now Publishers (2021). (IF: 65.3)
[Diagnostics] Lei, M., Li, J., Li, M., Zou, L. & Yu, H. An improved UNet++ model for congestive heart failure diagnosis using short-term RR intervals. Diagnostics, MDPI (2021). (IF: 3.992)
[Fuel] Lei, M., Rao, Z., Wang, H., Chen, Y., Zou, L. & Yu, H. Maceral groups analysis of coal based on sematic segmentation of photomicrographs via the improved U-net. Fuel, Elsevier (2021). (IF: 5.578)
[JRCS] Zhou, Q., Lim, F. J., Yu, H., Xu, G., Ren, X., Liu, D., Wang, X., Mai, X. & Xu, H. A study on factors affecting service quality and loyalty intention in mobile banking. Journal of Retailing and Consumer Services 60, doi:10.1016/j.jretconser.2020.102424, Elsevier (2021). (IF: 10.972) (8world News)
[P2PNA] Yin, X., Huang, J., He, W., Guo, W., Yu, H. & Cui, L. Group task allocation approach for heterogeneous software crowdsourcing tasks. Peer-to-Peer Networking and Applications 14(3), 1736–1747, Springer (2021). (IF: 3.488)
- 2020 -
[KBS] Yi, C., Xu, Y., Yu, H., Yan, Y. & Liu, Y. Multi-component transfer metric learning for handling unrelated source domain samples. Knowledge-Based Systems 203, doi:10.1016/j.knosys.2020.106132, Elsevier (2020). (IF: 8.139)
[IEEE TPDS] Lyu, L., Yu, J., Nandakumar, K., Li, Y., Ma, X., Jin, J., Yu, H. & Ng, K. S. Towards fair and privacy-preserving federated deep models. IEEE Transactions on Parallel and Distributed Systems 31(11), 2524–2541, IEEE (2020). (IF: 3.757) (Zhihu Article, Medium Article)
[IEEE TIM] Zou, L., Yu, X., Li, M., Lei, M. & Yu, H. Nondestructive identification of coal and gangue via near-infrared spectroscopy based on improved broad learning. IEEE Transactions on Instrumentation and Measurement 69(10), 8043–8052, IEEE (2020). (IF: 5.332)
[IEEE IS] 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), 58–69, IEEE (2020). (IF: 6.744)
[KBS] Feng, S., Yu, H. & Duarte, M. F. Autoencoder based sample selection for self-taught learning. Knowledge-Based Systems 192, doi:10.1016/j.knosys.2019.105343, Elsevier (2020). (IF: 8.139)
[ACM TIST] Wang, J., Chen, Y., Feng, W., Yu, H., Huang, M. & Yang, Q. Transfer learning with dynamic distribution adaptation. ACM Transactions on Intelligent Systems and Technology 11(1), 6:1–6:25, ACM (2020). (IF: 10.489) [ESI Highly Cited Paper]
[AI Mag.] Zheng, Y., Yu, H., Cui, L., Miao, C., Leung, C., Liu, Y. & Yang, Q. Addressing the challenges of government service provision with AI. AI Magazine 41(1), 33–43, AAAI Press (2020). (IF: 2.524) (Wechat Article)
- 2019 -
Guo, X., Yu, H., Chen, Y. & Miao, C. Weakly supervised neural representation learning through exploiting expert knowledge. International Journal of Information Technology 25(1), 1–9, SCS (2019).
[PMC] Chen, Y., Wang, J., Huang, M. & Yu, H. Cross-position activity recognition with stratified transfer learning. Pervasive and Mobile Computing 57, 1–13, Elsevier (2019). (IF: 3.848)
[IEEE Access] Wang, T., Yang, H., Yu, H., Zhou, W., Liu, Y. & Song, H. A revenue-maximizing bidding strategy for demand-side platforms. IEEE Access 7(1), 68692–68706, IEEE (2019). (IF: 3.476)
Yu, H. Ethics and AI: Teaching our machines to tell right from wrong. The IT Society 1, 2–3, Singapore Computer Society (2019). (商用AI)
[IEEE TKDE] Hu, C., Chen, Y., Peng, X., Yu, H., Gao, C. & Hu, L. A novel feature incremental learning method for sensor-based activity recognition. IEEE Transactions on Knowledge and Data Engineering 31(6), 1038–1050, IEEE (2019). (IF: 9.235)
[ACM TIST] Wang, W., Zheng, V. W., Yu, H. & Miao, C. A survey of zero-shot learning: Settings, methods and applications. ACM Transactions on Intelligent Systems and Technology 10(2), 13:1–13:19, ACM (2019). (IF: 10.489) (Wechat Article)
[IEEE Access] Jiang, S., Xu, Y., Wang, T., Yang, H., Qiu, S., Yu, H. & Song, H. Multi-label metric transfer learning jointly considering instance space and label space distribution divergence. IEEE Access 7(1), 10362–10373, IEEE (2019). (IF: 3.476)
- 2018 -
Deng, Z., Zhang, J. & Yu, H. A survey of ethics in resource allocation and crowdsourcing. International Journal of Information Technology 24(2), 1–17, SCS (2018).
Guo, X., Yu, H. & Chen, Y. Building a smart assistant for improving chronic pain management in primary care. International Journal of Information Technology 24(2), 1–16, SCS (2018).
Miao, C., Zeng, Z., Wu, Q., Yu, H. & Leung, C. Humanized artificial intelligence: What, why and how. International Journal of Information Technology 24(2), 1–21, SCS (2018).
Lin, J., Yu, H., Pan Z., Shen, Z. & Cui, L. Towards data-driven software engineering skills assessment. International Journal of Crowd Science 2(2), 123–135, Emerald (2018).
[IEEE TKDE] Chen, Y., Hu, C., Hu, B., Hu, L., Yu, H. & Miao, C. Inferring cognitive abilities from motor patterns. IEEE Transactions on Knowledge and Data Engineering 30(12), 2340–2353, IEEE (2018). (IF: 9.235)
[IEEE IoTJ] Shen, Z., Yu, H., Yu, L., Miao, C., Chen, Y. & Lesser, V. R. Dynamic generation of Internet of Things organizational structures through evolutionary computing. IEEE Internet of Things Journal 5(2), 943–954, IEEE (2018). (IF: 10.238)
- 2017 -
[npj Sci. Learn.] Yu, H., Miao, C., Leung, C. & White, T. J. Towards AI-powered personalization in MOOC learning. npj Science of Learning 2(15), doi:10.1038/s41539-017-0016-3, SpringerNature (2017). (IF: 5.513) (News Report)
[Sci. Rep.] Yu, H., Miao, C., Chen, Y., Fauvel, S., Li, X. & Lesser, V. R. Algorithmic management for improving collective productivity in crowdsourcing. Scientific Reports 7(12541), doi:10.1038/s41598-017-12757-x, SpringerNature (2017). (IF: 4.996)
Cui, L., Zhao, X., Liu, L., Yu, H. & Miao, Y. Complex crowdsourcing task allocation strategies employing supervised and reinforcement learning. International Journal of Crowd Science 1(2), 146–160, Emerald (2017).
[Sci. Data] Yu, H., Shen, Z., Miao, C., Leung, C., Chen, Y., Fauvel, S., Lin, J., Cui, L., Pan, Z. & Yang, Q. A dataset of human decision-making in teamwork management. Scientific Data 4(160127), doi:10.1038/sdata.2016.127, SpringerNature (2017). (IF: 8.501)
Mei, J.-P., Yu, H., Shen, Z. & Miao, C. A social influence based trust model for recommender systems. Intelligent Data Analysis 21(2), 263–277, IOS Press (2017).
- 2016 -
[Sci. Rep.] Yu, H., Miao, C., Leung, C., Chen, Y., Fauvel, S., Lesser, V. R. & Yang, Q. Mitigating herding in hierarchical crowdsourcing networks. Scientific Reports 6(4), doi:10.1038/s41598-016-0011-6, SpringerNature (2016). (IF: 4.996)
Zhang, W., Shi, Y., Liu, L., Zhang, S., Zheng, Y., Cui, L. & Yu, H. CTP: A scheduling strategy to smooth response time fluctuations in multi-tier website system. Microprocessors and Microsystems 47(A), 198–208, Elsevier (2016). (IF: 3.503)
Shi, Y., Zhang, K., Cui, L., Liu, L., Zheng, Y., Zhang, S. & Yu, H. MapReduce short jobs optimization based on resource reuse. Microprocessors and Microsystems 47(A), 178–187, Elsevier (2016).(IF: 3.503)
[Decis. Support Syst.] Miao, C., Yu, H., Shen, Z. & Leung, C. Balancing quality and budget considerations in mobile crowdsourcing. Decision Support Systems 90, 56–64, Elsevier (2016). (IF: 6.969)
- 2015 -
Lin, J., Yu, H., Zhang, L.& Shen, Z. Using Goal Net to model user stories in agile software development. International Journal of Information Technology 21(2), 1–17, SCS (2015).
- 2014 -
[Decis. Support Syst.] Yu, H., Shen, Z., Miao, C., An, B. & Leung, C. Filtering trust opinions through reinforcement learning. Decision Support Systems 66, 102–113, Elsevier (2014). (IF: 6.969)
- 2013 -
[IEEE Access] Yu, H., Shen, Z., Leung, C., Miao, C. & Lesser, V. R. A survey of multi-agent trust management systems. IEEE Access 1(1), 35–50, IEEE (2013). (IF: 3.476)
Yu, H., Shen, Z., Zhang, L. & Miao, C. Towards health care service ecosystem management for the elderly. International Journal of Information Technology 19(2), 1–16, SCS (2013).
Ji, J., Yu, H., Li, B., Shen, Z. & Miao, C. Learning Chinese characters with gestures. International Journal of Information Technology 19(1), 1–11, SCS (2013).
- 2012 -
Cheng, P., Yu, H., Shen, Z. & Liu, Z. An interactive 3D product design tool for mobile pre-commerce environments. International Journal of Information Technology 18(2), 1–9, SCS (2012).
Leung, C., Miao, C., Yu, H. & Helander, M. Towards an ageless computing ecosystem. International Journal of Information Technology 18(1), 1–20, SCS (2012).
- 2011 -
Pan, L., Meng, X., Shen, Z. & Yu, H. A reputation-based trust aware web service interaction pattern for manufacturing grids. International Journal of Information Technologies 17(1), 1–8, SCS (2011).
Shen, Z., Yu, H., Miao, C. & Weng, J. Trust-based web-service selection in virtual communities. Web Intelligence and Agent Systems 9(3), 227–238, IOS Press (2011).
- 2010 -
[Proc. IEEE] Yu, H., Shen, Z., Miao, C., Leung, C. & Niyato, D. A survey of trust and reputation management systems in wireless communications. Proceedings of the IEEE 98(10), 1755–1772, IEEE (2010). (IF: 25.6) [ESI Highly Cited Paper]
Yu, H., Shen, Z. & Leung, C. Towards trust-aware health monitoring body area sensor networks. International Journal of Information Technology 16(2), 1–20, SCS (2010). (Best Student Paper Award)
- 2009 -
Qin, T., Yu, H., Leung, C., Shen, Z. & Miao, C. Towards a trust aware cognitive radio architecture. ACM SIGMOBILE Mobile Computing and Communications Review 13(2), 86–95, ACM (2009).
- 2008 -
Yu, H., Shen, Z. & Miao, C. A goal oriented development tool to automate the incorporation of intelligent agents into interactive digital media applications. ACM Computers in Entertainment 6(2), pp. 24:1–24:15, ACM (2008).