Publications
arXiv Preprints
- L. Yi, H. Yu, C. Ren, H. Zhang, G. Wang, X. Liu & X. Li, "pFedAFM: Adaptive Feature Mixture for Batch-Level Personalization in Heterogeneous Federated Learning," arXiv preprint arXiv:2404.17847, 2024.
- C. Ren, H. Yu, H. Peng, X. Tang, B. Zhao, L. Yi, A. Z. Tan, Y. Gao, A. Li, X. Li, Z. Li & Q. Yang, "Advances and Open Challenges in Federated Foundation Models," arXiv preprint arXiv:2404.15381, 2024.
- L. Yi, H. Yu, C. Ren, H. Zhang, G. Wang, X. Liu & X. Li, "pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning," arXiv preprint arXiv:2402.01350, 2024.
- L. Yi, H. Yu, G. Wang & X. Liu, "pFedES: Model Heterogeneous Personalized Federated Learning with Feature Extractor Sharing," arXiv preprint arXiv:2311.06879, 2023.
- L. Yi, H. Yu, G. Wang, X. Liu & X. Li, "pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning," arXiv preprint arXiv:2310.13283, 2023.
- C. Ren, H. Yu, R. Yan, M. Xu, Y. Shen, H. Zhu, D. Niyato, Z. Y. Dong & L. C. Kwek, "Towards Quantum Federated Learning," arXiv preprint arXiv:2306.09912, 2023.
- A. Li, R. Liu, M. Hu, L. A. Tuan & H. Yu, "Towards Interpretable Federated Learning," arXiv preprint arXiv:2302.13473, 2023.
- X. Guo & H. Yu, "On the Domain Adaptation and Generalization of Pretrained Language Models: A Survey," arXiv preprint arXiv:2211.03154, 2022.
- P. S. Kyaw & H. Yu, "Personalised Federated Learning: A Combinational Approach," arXiv preprint arXiv:2108.09618, 2021.
Journal Articles
- Xiaoli Tang & Han Yu. Towards trustworthy AI-empowered real-time bidding for online advertisement auctioning. ACM Computing Surveys, ACM (2024). [IF: 23.8]
- Xiaoli Tang & Han Yu. A cost-aware utility-maximizing bidding strategy for auction-based federated learning. IEEE Transactions on Neural Networks and Learning Systems, IEEE (2024). [IF: 10.2]
- Chao Ren, Zhao Yong Dong, Han Yu, Minrui Xu, Zehui Xiong & Dusit Niyato. 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, IEEE (2024). [IF: 8.6]
- Yulan Gao, Ziqiang Ye & Han Yu. Cost-efficient computation offloading in SAGIN: A deep reinforcement learning and perception-aided approach. IEEE Journal on Selected Areas in Communications, IEEE (2024). [IF: 13.8]
- Anran Li, Guangjing Wang, Ming Hu, Jianfei Sun, Lan Zhang, Luu Anh Tuan & Han Yu. Joint client-and-sample selection for federated learning via bi-level optimization. IEEE Transactions on Mobile Computing, IEEE (2024). [IF: 7.7]
- Yuanlu Chen, Alysa Tan, Siwei Feng, Han Yu, Tao Deng, Libang Zhao & Feng Wu. General federated class-incremental learning with lightweight generative replay. IEEE Internet of Things Journal, vol. 11, no. 20, pp. 33927-33939, IEEE (2024). [IF: 8.2]
- Xiaoli Tang & Han Yu. Efficient large-scale personalizable bidding for multi-agent auction-based federated learning. IEEE Internet of Things Journal, vol. 11, no. 15, pp. 26518-26530, IEEE (2024). [IF: 10.6]
- Jie Zheng, Jipeng Xu, Hongyang Du, Dusit Niyato, Jiawen Kang, Jiangtian Nie & Zheng Wang. Trust management of tiny federated learning in Internet of unmanned aerial vehicles. IEEE Internet of Things Journal, vol. 11, no. 12, pp. 21046-21060, IEEE (2024). [IF: 10.6]
- Liping Yi, Xiaorong Shi, Nan Wang, Gang Wang, Xiaoguang Liu, Zhuan Shi & Han Yu. pFedKT: Personalized federated learning with dual knowledge transfer. Knowledge-Based Systems, Elsevier (2024). [IF: 8.8]
- Anran Li, Yuanyuan Chen, Jian Zhang, Mingfei Cheng, Yihao Huang, Yueming Wu, Anh Tuan Luu & Han Yu. Historical embedding-guided efficient large-scale federated graph learning. Proceedings of the ACM on Management of Data, vol. 2, no. 3, pp. 144:1-144:24, ACM (2024).
- Qianyu Li, Bozheng Feng, Xiaoli Tang, Han Yu & Hengjie Song. MuLAN: Multi-level attention-enhanced matching network for few-shot knowledge graph completion. Neural Networks, Elsevier (2024). [IF: 7.8]
- Rui Liu, Pengwei Xing, Zichao Deng, Anran Li, Cuntai Guan & Han Yu. Federated graph neural networks: Overview, techniques and challenges. IEEE Transactions on Neural Networks and Learning Systems, IEEE (2024). [IF: 10.4]
- Sheng Liu, Linlin You, Rui Zhu, Bing Liu, Rui Liu, Han Yu & Chau Yuen. AFM3D: An asynchronous federated meta-learning framework for driver distraction detection. IEEE Transactions on Intelligent Transportation Systems, IEEE (2024). [IF: 8.5]
- Rui Liu, Yuanyuan Chen, Anran Li, Yi Ding, Han Yu & Cuntai Guan. Aggregating intrinsic information to enhance BCI performance through federated learning. Neural Networks, Elsevier (2024). [IF: 7.8]
- Nan Zhao, Yiyang Pei, Ying-Chang Liang & Dusit Niyato. Deep-reinforcement-learning-based contract incentive mechanism for joint sensing and computation in mobile crowdsourcing networks. IEEE Internet of Things Journal, vol. 11, no. 7, pp. 12755-12767, IEEE (2024). [IF: 10.6]
- Chao Ren, Rudai Yan, Minrui Xu, Han Yu, Yan Xu, Dusit Niyato & Zhao Yang Dong. QFDSA: A quantum-secured federated learning system for smart grid dynamic security assessment. IEEE Internet of Things Journal, vol. 11, no. 5, pp. 8414-8426, IEEE (2024). [IF: 10.6]
- Wenxuan Li, Shihan Dou, Yueming Wu, Chenxi Li & Yang Liu. COCL: An intelligent framework for enhancing deep learning-based vulnerability detection. IEEE Transactions on Industrial Informatics, vol. 20, no. 3, pp. 4953-4961, IEEE (2024). [IF: 12.3]
- Jiawen Kang, Jinbo Wen, Dongdong Ye, Bingkun Lai, Tianhao Wu, Zehui Xiong, Jiangtian Nie, Dusit Niyato, Yang Zhang & Shengli Xie. Blockchain-empowered federated learning for healthcare metaverses: User-centric incentive mechanism with optimal data freshness. IEEE Transactions on Cognitive Communications and Networking, vol. 10, no. 1, pp. 348-362, IEEE (2024). [IF: 8.6]
- Xinjing Song, Di Wang, Chai Quek, Ah-Hwee Tan & Yanjiang Wang. Spatial-temporal episodic memory modeling for ADLs: encoding, retrieval, and prediction. Complex & Intelligent Systems, SpringerNature (2023). [IF: 5.8]
- Hong Xu, Maohao Che, Sze Yee Ashley Say, Han Yu, Qingji Zhou, Jared Shu, Wen Sun & Xi Luo. Investigating customers' continuous trust towards mobile banking apps. Humanities and Social Sciences Communications, SpringerNature (2023). [IF: 3.5]
- Chao Ren, Chunran Zou, Zehui Xiong, Han Yu, Zhao Yang Dong & Dusit Niyato. 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]
- Anran Li, Jiahui Huang, Ju Jia, Hongyi Peng, Lan Zhang, Luu Anh Tuan, Han Yu & Xiang-Yang Li. Efficient and privacy-preserving feature importance-based vertical federated learning. IEEE Transactions on Mobile Computing, doi:10.1109/TMC.2023.3333879, IEEE (2023). [IF: 7.9]
- Anran Li, Yue Cao, Jiabao Guo, Hongyi Peng, Qing Guo & Han Yu. FedCSS: Joint client-and-sample selection for hard sample-aware noise-robust federated learning. Proceedings of the ACM on Management of Data, vol. 1, no. 3, pp. 212:1-212:24, ACM (2023).
- Tianlin Li, Xiaofei Xie, Jian Wang, Qing Guo, Aishan Liu, Lei Ma & Yang Liu. Faire: Repairing fairness of neural networks via neuron condition synthesis. ACM Transactions on Software Engineering and Methodology, ACM (2023). [IF: 4.4]
- Francisco Munguia-Galeano, Ah-Hwee Tan & Ze Ji. Deep reinforcement learning with explicit context representation. IEEE Transactions on Neural Networks and Learning Systems, IEEE (2023). [IF: 10.4]
- Chao Ren, Han Yu, Rudai Yan, Qiaoqiao Li, Yan Xu, Dusit Niyato & Zhao Yang Dong. SecFedSA: A secure differential privacy-based federated learning approach for smart cyber-physical grid stability assessment. IEEE Internet of Things Journal, IEEE (2023). [IF: 10.6]
- Rakpong Kaewpuang, Minrui Xu, Wei Yang Bryan Lim, Dusit Niyato, Han Yu, Jiawen Kang & Xuemin Sherman Shen. Cooperative resource management in quantum key distribution networks for semantic communication. IEEE Internet of Things Journal, doi:10.1109/JIOT.2023.3301033, IEEE (2023). [IF: 10.6]
- Qianyu Li, Jiale Yao, Xiaoli Tang, Han Yu, Siyu Jiang, Haizhi Yang & Hengjie Song. Capsule neural tensor networks with multi-aspect information for few-shot knowledge graph completion. Neural Networks, vol. 164, pp. 323-334, Elsevier (2023). [IF: 9.657]
- Chang'an Yi, Haotian Chen, Yonghui Xu, Huanhuan Chen, Yong Liu, Haishu Tan, Yuguang Yan & Han Yu. Multi-component adversarial domain adaptation: A general framework. IEEE Transactions on Neural Networks and Learning Systems, IEEE (2023). [IF: 14.255]
- Yijing Lin, Zhipeng Gao, Hongyang Du, Jiawen Kang, Dusit Niyato, Qian Wang, Jingqing Ruan & Shaohua Wan. DRL-based adaptive sharding for blockchain-based federated fearning. IEEE Transactions on Communications, IEEE (2023). [IF: 8.3]
- Yuxin Shi, Han Yu & Cyril Leung. Towards fairness-aware federated learning. IEEE Transactions on Neural Networks and Learning Systems, doi:10.1109/TNNLS.2023.3263594, IEEE (2023). [IF: 14.255]
- Ronghong Mo, Yiyang Pei, Neelakantam Venkatarayalu, Pereira Nathaniel Joseph, A. Benjamin Premkumar, Sumei Sun & Simon Kok Kan Foo. Unsupervised TCN-AE-Based Outlier Detection for Time Series With Seasonality and Trend for Cellular Networks. IEEE Transactions on Wireless Communications, IEEE (2023). [IF: 10.4]
- Chang Liu & Han Yu. AI-empowered persuasive video generation: A survey. ACM Computing Surveys, vol. 55, no. 13, pp. 285:1-285:31, ACM (2023). [IF: 16.062]
- Jiehuang Zhang, Ying Shu & Han Yu. Fairness in Design: A framework for facilitating ethical AI designs. International Journal of Crowd Science, vol. 7, no. 1, pp. 32-39, Tsinghua University Press (2023). (Excellent Paper Award)
- Zelei Liu, Yuanyuan Chen, Yansong Zhao, Han Yu, Yang Liu, Renyi Bao, Jinpeng Jiang, Zaiqing Nie, Qian Xu & Qiang Yang. CAreFL: Enhancing smart healthcare with contribution-aware federated learning. AI Magazine, doi:10.1002/aaai.12082, AAAI Press (2023). [IF: 2.524]
- Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan & Chai Quek. Value-based subgoal discovery and path planning for reaching long-horizon goals. IEEE Transactions on Neural Networks and Learning Systems, IEEE (2023). [IF: 14.255]
- Tengyun Wang, Haizhi Yang, Yang Liu, Han Yu & Hengjie Song. A multimodal approach for improving market price estimation in online advertising. Knowledge-Based Systems, vol. 266, doi:10.1016/j.knosys.2023.110392, Elsevier (2023). [IF: 8.139]
- Shiyao Ma, Jiangtian Nie, Jiawen Kang, Lingjuan Lyu, Ryan Wen Liu, Ruihui Zhao, Ziyao Liu & Dusit Niyato. Privacy-preserving anomaly detection in cloud manufacturing via federated transformer. IEEE Transactions on Industrial Informatics, IEEE (2022). [IF: 11.648]
- Napat Ngoenriang, Minrui Xu, Jiawen Kang, Dusit Niyato, Han Yu & Sherman Shen. DQC2O: Distributed quantum computing for collaborative optimization in future networks. IEEE Communications Magazine, IEEE (2023). [IF: 9.03]
- Rakpong Kaewpuang, Suttinee Sawadsitang, Dusit Niyato & Han Yu. Evolutionary carrier selection for shared truck delivery services. IEEE Transactions on Vehicular Technology, IEEE (2022). [IF: 6.239]
- Lingjuan Lyu, Han Yu, Xingjun Ma, Chen Chen, Lichao Sun, Jun Zhao, Qiang Yang & Philip S. Yu. Privacy and robustness in federated learning: Attacks and defenses. IEEE Transactions on Neural Networks and Learning Systems, doi:10.1109/TNNLS.2022.3216981, IEEE (2022). [IF: 14.255]
- Eunil Seo, Dusit Niyato & Erik Elmroth. Resource-efficient federated learning with non-IID data: An auction theoretic approach. IEEE Internet of Things Journal, IEEE (2022). [IF: 10.238]
- Jiawen Kang, Hongyang Du, Zonghang Li, Zehui Xiong, Shiyao Ma, Dusit Niyato & Yuan Li. Personalized saliency in task-oriented semantic communications: Image transmission and performance analysis. IEEE Journal on Selected Areas in Communications, IEEE (2022). [IF: 13.081]
- Jiawen Kang, Xuandi Li, Jiangtian Nie, Yi Liu, Minrui Xu, Zehui Xiong, Dusit Niyato & Qiang Yan. Communication-efficient and cross-chain empowered federated learning for artificial intelligence of things. IEEE Transactions on Network Science and Engineering, IEEE (2022). [IF: 5.033]
- Kan Xie, Zhe Zhang, Bo Li, Jiawen Kang, Dusit Niyato, Shengli Xie & Yi Wu. Efficient federated learning with spike neural networks for traffic sign recognition. IEEE Transactions on Vehicular Technology, IEEE (2022). [IF: 6.239]
- Haoran Shi, Yonghui Xu, Yali Jiang, Han Yu & Lizhen Cui. Efficient asynchronous multi-participant vertical federated learning. IEEE Transactions on Big Data, IEEE (2022). [IF: 7.2]
- Xavier Tan, Wei Chong Ng, Wei Yang Bryan Lim, Zehui Xiong, Dusit Niyato & Han Yu. Reputation-aware federated learning client selection based on stochastic integer programming. IEEE Transactions on Big Data, doi:10.1109/TBDATA.2022.3191332, IEEE (2022). [IF: 7.2]
- Pengwei Xing, Songtao Lu, Lingfei Wu & Han Yu. BiG-Fed: Bilevel optimization enhanced graph-aided federated learning. IEEE Transactions on Big Data, IEEE (2022). [IF: 7.2]
- Siwei Feng, Boyang Li, Han Yu, Yang Liu & Qiang Yang. Semi-supervised federated heterogeneous transfer learning. Knowledge-Based Systems, vol. 252, doi:10.1016/j.knosys.2022.109384, Elsevier (2022). [IF: 8.139]
- Xiaohu Wu & Han Yu. MarS-FL: Enabling competitors to collaborate in federated learning. IEEE Transactions on Big Data, doi:10.1109/TBDATA.2022.3186991, IEEE (2022). [IF: 7.2]
- Yining Wang, Mingzhe Chen, Tao Luo, Walid Saad, Dusit Niyato, H. Vincent Poor & Shuguang Cui. Performance optimization for semantic communications: An attention-based reinforcement learning approach. IEEE Journal on Selected Areas in Communications, vol. 40, no. 9, pp. 2598-2613, IEEE (2022). [IF: 13.081]
- Yue Hu, Budhitama Subagdja, Ah-Hwee Tan, Chai Quek & Quanjun Yin. Who Are the 'Silent Spreaders'?: Contact Tracing in Spatio-Temporal Memory Models. Neural Computing and Applications, vol. 4, pp. 14859-14879, Springer (2022). [IF: 5.102]
- Felix Juefei-Xu, Run Wang, Yihao Huang, Qing Guo, Lei Ma & Yang Liu. Countering malicious deepFakes: Survey, battleground, and horizon. International Journal of Computer Vision, vol. 130, pp. 1678-1734, Springer (2022). [IF: 13.369]
- Haizhi Yang, Siyu Jiang, Yueyue Shi, Qianyu Li, Xiaoli Tang, Han Yu & Hengjie Song. Kaplan-Meier Markov network: Learning the distribution of market price by censored data in online advertising. Knowledge-Based Systems, doi:10.1016/j.knosys.2022.109248, Elsevier (2022). [IF: 8.139]
- Nguyen Quang Hieu, Dinh Thai Hoang, Dusit Niyato, Ping Wang, Dong In Kim & Chau Yuen. Transferable deep reinforcement learning framework for autonomous vehicles with joint radar-data communications. IEEE Transactions on Communications, vol. 70, no. 8, pp. 5164-5180, IEEE (2022). [IF: 6.166]
- Nan Zhao, Zhiyang Ye, Yiyang Pei, Ying-Chang Liang & Dusit Niyato. Multi-agent deep reinforcement learning for task offloading in UAV-assisted mobile edge computing. IEEE Transactions on Wireless Communications, vol. 21, no. 9, pp. 6949-6960, IEEE (2022). [IF: 8.346]
- Shaohan Feng, Xiao Lu, Sumei Sun & Dusit Niyato. Mean-field artificial noise assistance and uplink power control in covert IoT systems. IEEE Transactions on Wireless Communications, vol. 21, no. 9, pp. 7358-7373, IEEE (2022). [IF: 8.346]
- Wenbo Wang, Amir Leshem, Dusit Niyato & Zhu Han. Decentralized learning for channel allocation in IoT networks over unlicensed bandwidth as a contextual multi-player multi-armed bandit game. IEEE Transactions on Wireless Communications, vol. 21, no. 5, pp. 3162-3178, IEEE (2022). [IF: 8.346]
- Zelei Liu, Yuanyuan Chen, Han Yu, Yang Liu & Lizhen Cui. GTG-Shapley: Efficient and accurate participant contribution evaluation in federated learning. ACM Transactions on Intelligent Systems and Technology, vol. 13, no. 4, pp. 60:1-60:21, ACM (2022). [IF: 10.489]
- Xu Guo, Han Yu, Boyang Li, Hao Wang, Pengwei Xing, Siwei Feng, Zaiqing Nie & Chunyan Miao. Federated learning for personalized humor recognition. ACM Transactions on Intelligent Systems and Technology, vol. 13, no. 4, pp. 68:1-68:18, ACM (2022). [IF: 10.489] (PREMIA Certificate of Commendation)
- Bozhi Wu, Shangqing Liu, Ruitao Feng, Xiaofei Xie, Jingkai Siow & Shang-Wei Lin. Enhancing security patch identification by capturing structures in commits. IEEE Transactions on Dependable and Secure Computing, IEEE (2022). [IF: 6.791]
- Ju Jia, Yueming Wu, Anran Li, Siqi Ma & Yang Liu. Subnetwork-lossless robust watermarking for hostile theft attacks in deep transfer learning models. IEEE Transactions on Dependable and Secure Computing, IEEE (2022). [IF: 6.791]
- Tianze Luo, Zichen Chen, Budhitama Subagdja & Ah-Hwee Tan. Real-time hierarchical map segmentation for coordinating multi-robot exploration. IEEE Access, IEEE (2022). [IF: 3.476]
- Yuan-Ai Xie, Jiawen Kang, Dusit Niyato, Nguyen Thi Thanh Van, Nguyen Cong Luong, Zhixin Liu & Han Yu. Securing federated learning: A covert communication-based approach. IEEE Network, IEEE (2022). [IF: 10.294]
- Ryan Wen Liu, Maohan Liang, Jiangtian Nie, Yanli Yuan, Zehui Xiong, Han Yu & Nadra Guizani. STMGCN: Mobile edge computing-empowered vessel trajectory prediction using spatio-temporal multi-graph convolutional network. IEEE Transactions on Industrial Informatics, IEEE (2022). [IF: 11.648]
- Alysa Ziying Tan, Han Yu, Lizhen Cui & Qiang Yang. Towards personalized federated learning. IEEE Transactions on Neural Networks and Learning Systems, doi:10.1109/TNNLS.2022.3160699, IEEE (2022). [IF: 14.255]
- Chen Chen, Lingjuan Lyu, Han Yu & Gang Chen. Practical attribute reconstruction attack against federated learning. IEEE Transactions on Big Data, doi:10.1109/TBDATA.2022.3159236, IEEE (2022). [IF: 7.2]
- Ka Lon Sou, Ashley Say & Hong Xu. Unity assumption in audiovisual emotion perception. Frontiers in Neuroscience, Frontiers (2022). [IF: 5.152]
- Wei Chong Ng, Wei Yang Bryan Lim, Zehui Xiong, Dusit Niyato, Chunyan Miao, Zhu Han & Dong In Kim. Stochastic coded offloading scheme for unmanned aerial vehicle-assisted edge computing. IEEE Internet of Things Journal, IEEE (2022). [IF: 10.238]
- Ryan Wen Liu, Yu Guo, Jiangtian Nie, Qin Hu, Zehui Xiong, Han Yu & Mohsen Guizani. Intelligent edge-enabled efficient multi-source data fusion for autonomous surface vehicles in maritime Internet of Things. IEEE Transactions on Green Communications and Networking, doi:10.1109/TGCN.2022.3158004, IEEE (2022). [IF: 3.525]
- Xiaofei Xie, Tianlin Li, Jian Wang, Lei Ma, Qing Guo, Felix Juefei-Xu & Yang Liu. NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks. ACM Transactions on Software Engineering and Methodology, vol. 31, no. 3, pp. 47:1-47:27, ACM (2022). [IF: 4.267]
- Yihao Huang, Felix Juefei-Xu, Qing Guo, Yang Liu & Geguang Pu. FakeLocator: Robust localization of GAN-based face manipulations. IEEE Transactions on Information Forensics and Security, IEEE (2022). [IF: 7.231]
- Yaqin Zhou, Jing Kai Siow, Chenyu Wang, Shangqing Liu & Yang Liu. SPI: Automated identification of security patches via commits. ACM Transactions on Software Engineering and Methodology, vol. 31, no. 1., pp. 13:1-13:27, ACM (2022). [IF: 4.267]
- Bo Yang, Xuelin Cao, Chongwen Huang, Yong Liang Guan, Chau Yuen, Marco Di Renzo, Dusit Niyato, Merouane Debbah & Lajos Hanzo. Spectrum learning-aided reconfigurable intelligent surfaces for 'green' 6G networks. IEEE Network, vol. 35, no. 6, pp. 20-26, IEEE (2021). [IF: 10.294]
- Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong, Dusit Niyato, Chunyan Miao & Dong In Kim. Dynamic edge association and resource allocation in self-organizing hierarchical federated learning networks. IEEE Journal on Selected Areas in Communications, vol. 39, no. 12, pp. 3640-3653, IEEE (2021). [IF: 13.081]
- Lotfi Ismail, Dusit Niyato, Sumei Sun, Dinh Thai Hoang, Yonghui Li & Dong In Kim. Protecting multi-function wireless systems from jammers with backscatter assistance: An intelligent strategy. IEEE Transactions on Vehicular Technology, vol. 70, no. 11, pp. 11812-11826, IEEE (2021). [IF: 6.239]
- Nan Zhao, Aonan Wu, Yiyang Pei, Ying-Chang Liang & Dusit Niyato. Spatial-temporal aggregation graph convolution network for efficient mobile cellular traffic prediction. IEEE Communications Letters, vol. 26, no. 3, pp. 587-591, IEEE (2021). [IF: 3.553]
- Yang Liu, Anbu Huang, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu & Qiang Yang. Federated learning-powered visual object detection for safety monitoring. AI Magazine, vol. 42, no. 2, pp. 19-27, AAAI Press (2021). [IF: 2.524]
- Yongqing Zheng, Han Yu, Yuliang Shi, Kun Zhang, Shuai Zhen, Lizhen Cui, Cyril Leung & Chunyan Miao. Optimizing smart grid operations from the demand side. AI Magazine, vol. 42, no. 2, pp. 28-37, AAAI Press (2021). [IF: 2.524]
- Anxiang Zeng, Han Yu, Qing Da, Yusen Zhan, Yang Yu, Zhihua Zhou & Chunyan Miao. Improving search engine efficiency through contextual factor selection. AI Magazine, vol. 42, no. 2, pp. 50-58, AAAI Press (2021). [IF: 2.524]
- Yuan Liu, Xin Zou & Han Yu. 3R Model: A post-purchase context-aware reputation model to mitigate unfair ratings in e-commerce. Knowledge-Based Systems, vol. 231, doi:10.1016/j.knosys.2021.107441, Elsevier (2021). [IF: 8.139]
- Shangwei Guo, Tianwei Zhang, Guowen Xu, Han Yu, Tao Xiang & Yang Liu. Byzantine-resilient decentralized stochastic gradient descent. IEEE Transactions on Circuits and Systems for Video Technology, doi:10.1109/TCSVT.2021.3116976, IEEE (2021). [IF: 5.859]
- Shangwei Guo, Tianwei Zhang, Guowen Xu, Han Yu, Tao Xiang & Yang Liu. Topology-aware differential privacy for decentralized image classification. IEEE Transactions on Circuits and Systems for Video Technology, doi:10.1109/TCSVT.2021.3105723, IEEE (2021). [IF: 5.859]
- Wei Yang Bryan Lim, Sahil Garg, Zehui Xiong, Yang Zhang, Dusit Niyato, Cyril Leung & Chunyan Miao. UAV-assisted communication efficient federated learning in the era of the artificial intelligence of things. IEEE Network, doi:10.1109/MNET.002.2000334, IEEE (2021). [IF: 10.294]
- Guangda Huzhang, Zhen-Jia Pang, Yongqing Gao, Yawen Liu, Weijie Shen, Wen-Ji Zhou, Qianying Lin, Qing Da, An-Xiang Zeng, Han Yu, Yang Yu & Zhi-Hua Zhou. AliExpress Learning-To-Rank: Maximizing online model performance without going online. IEEE Transactions on Knowledge and Data Engineering, doi:10.1109/TKDE.2021.3098898, IEEE (2021). [IF: 9.235]
- Haizhi Yang, Tengyun Wang, Xiaoli Tang, Han Yu, Fei Liu & Hengjie Song. Dynamically optimizing display advertising profits under diverse budget settings. IEEE Transactions on Knowledge and Data Engineering, doi:10.1109/TKDE.2021.3077699, IEEE (2021). [IF: 9.235]
- Yupeng Cheng, Qing Guo, Felix Juefei-Xu, Wei Feng, Shang-wei Lin, Weisi Lin & Yang Liu. Pasadena: Perceptually aware and stealthy adversarial denoise attack. IEEE Transactions on Multimedia, doi:10.1109/TMM.2021.3108009, IEEE (2021). [IF: 8.182]
- Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan & Chai Quek. End-to-End Hierarchical Reinforcement Learning With Integrated Subgoal Discovery. IEEE Transactions on Neural Networks and Learning Systems, doi:10.1109/TNNLS.2021.3087733, IEEE (2021). [IF: 14.255]
- Yue Hu , Budhitama Subagdja, Ah-Hwee Tan & Quanjun Yin. Vision-based topological mapping and navigation with self-organizing neural networks. IEEE Transactions on Neural Networks and Learning Systems, doi:10.1109/TNNLS.2021.3084212, IEEE (2021). [IF: 14.255]
- Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan & Chai Quek. Hierarchical reinforcement learning: A comprehensive survey. ACM Computing Surveys, vol. 54, no. 5, 109:1-109:35, ACM (2021). [IF: 16.062] (PREMIA Certificate of Commendation)
Conference Publications
- Liping Yi, Han Yu, Chao Ren, Gang Wang, Xiaoguang Liu & Xiaoxiao Li, "Federated Model Heterogeneous Matryoshka Representation Learning," in Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS'24), 2024.
- Mengmeng Chen, Xiaohu Wu, Xiaoli Tang, Tiantian He, Yew-Soon Ong, Qiqi Liu, Qicheng Lao & Han Yu, "Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning," in Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS'24), 2024.
- Xiaoli Tang, Han Yu, Xiaoxiao Li & Sarit Kraus, "Intelligent Agents for Auction-based Federated Learning: A Survey," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 8253-8261, 2024.
- Xiaoli Tang, Han Yu, Zengxiang Li & Xiaoxiao Li, "A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 4991-4999, 2024.
- Xiaoli Tang, Han Yu, Run Tang, Chao Ren, Anran Li & Xiaoxiao Li, "Dual Calibration-based Personalised Federated Learning," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 4982-4990, 2024.
- Liping Yi, Han Yu, Zhuan Shi, Gang Wang, Xiaoguang Liu, Lizhen Cui & Xiaoxiao Li, "FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 5371-5379, 2024.
- Xianjie Guo, Kui Yu, Hao Wang, Lizhen Cui, Han Yu & Xiaoxiao Li, "Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection," in Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), pp. 4071-4079, 2024.
- Hongyi Peng, Han Yu, Xiaoli Tang & Xiaoxiao Li, "FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler," in Proceedings of the 41st International Conference on Machine Learning (ICML'24), 2024.
- Pengwei Xing, Songtao Lu & Han Yu, "Federated Neuro-Symbolic Learning," in Proceedings of the 41st International Conference on Machine Learning (ICML'24), 2024.
- Shihan Dou, Yueming Wu, Haoxiang Jia, Yuhao Zhou, Yan Liu & Yang Liu, "CC2Vec: Combining Typed Tokens with Contrastive Learning for Effective Code Clone Detection," in Proceedings of the 30th Fast Software Encryption Conference (FSE'24), 2024.
- Jianfu Zhang, Qingtao Yu, Yizhou Chen, Guoliang Zhou, Yawei Sun, Chen Liang, Yawen Liu, Guangda Huzhang, Yabo Ni, Anxiang Zeng & Han Yu, "An E-Commerce Dataset Revealing Variations during Sales," in Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'24), pp. 1162-1171, 2024.
- Alysa Ziying Tan, Siwei Feng & Han Yu, "FL-CLIP: Bridging Plasticity and Stability in Pre-Trained Federated Class-Incremental Learning Models," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
- Yulan Gao, Zhaoxiang Hou, Chengyi Yang, Zengxiang Li, Han Yu & Xiaoxiao Li, "The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Foundation Models," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
- Xiaoli Tang, Han Yu & Xiaoxiao Li, "Agent-oriented Joint Decision Support for Data Owners in Auction-based Federated Learning," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
- Qianyu Li, Xiaoli Tang, Siyao Zhou, Han Yu, Hengjie Song, Lizhen Cui & Xiaoxiao Li, "FedRMS: Privacy-Preserving Federated Knowledge Graph Embedding through Randomization," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
- Zhiwei Xiong, Yunfan Zhang, Zhiqi Shen, Peiran Ren & Han Yu, "Multi-modal Learnable Queries for Image Aesthetics Assessment," in Proceedings of the 2024 IEEE International Conference on Multimedia and Expo (ICME'24), 2024.
- Yansong Zhao, Siyao Zhou, Yulan Gao & Han Yu, "A Fair Incentive Mechanism for Federated Auctioning Networks," in Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN'24), 2024.
- Xiaoli Tang & Han Yu, "Multi-Session Multi-Objective Budget Optimization for Auction-Based Federated Learning," in Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN'24), 2024.
- Xavier Tan & Han Yu, "Hire When You Need to: Gradual Participant Recruitment for Auction-Based Federated Learning," in Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN'24), 2024.
- Qianyu Li, Jiebin Chen, Xiaoli Tang, Han Yu & Hengjie Song, "Modeling Time Decay Effect in Temporal Knowledge Graphs via Multivariate Hawkes Process," in Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN'24), 2024.
- Doudou Wu, Shubham Pateria, Budhitama Subagdja & Ah-Hwee Tan, "FedSTEM-ADL: A Federated Spatial-Temporal Episodic Memory Model for ADL Prediction," in Proceedings of the 2024 International Joint Conference on Neural Networks (IJCNN'24), 2024.
- Chao Ren, Minrui Xu, Han Yu, Zehui Xiong, Zhenyong Zhang & Dusit Niyato, "Variational Quantum Circuit and Quantum Key Distribution-based Quantum Federated Learning: A Case of Smart Grid Dynamic Security Assessment," in Proceedings of the 2024 IEEE International Conference on Communications (ICC'24), 2024.
- Ming Hu, Peiheng Zhou, Zhihao Yue, Zhiwei Ling, Yihao Huang, Anran Li, Yang Liu, Xiang Lian & Mingsong Chen, "FedCross: Towards Accurate Federated Learning via Multi-Model Cross-Aggregation," in Proceeding of the 40th International Conference on Data Engineering (ICDE'24), pp. 2137-2150, 2024.
- Yuxin Shi & Han Yu, "Fairness-Aware Job Scheduling for Multi-Job Federated Learning," in Proceedings of the 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'24), 2024.
- Zichao Deng & Han Yu, "Noise-Resistant Graph Neural Network for Node Classification," in Proceedings of the 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'24), 2024.
- Zhiwei Xiong, Yunfan Zhang, Zhiqi Shen, Peiran Ren & Han Yu, "Image Aesthetics Assessment via Learnable Queries," in Proceedings of the 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'24), 2024.
- Siyue Feng, Wenqi Suo, Yueming Wu, Deqing Zou, Yang Liu & Hai Jin, "Machine Learning is All You Need: A Simple Token-based Approach for Effective Code Clone Detection," in Proceedings of the IEEE/ACM 46th International Conference on Software Engineering (ICSE'24), pp. 222:1-222:13, 2024.
- Yuqiang Sun, Daoyuan Wu, Yue Xue, Han Liu, Haijun Wang, Zhengzi Xu, Xiaofei Xie & Yang Liu, "GPTScan: Detecting Logic Vulnerabilities in Smart Contracts by Combining GPT with Program Analysis," in Proceedings of the IEEE/ACM 46th International Conference on Software Engineering (ICSE'24), pp. 166:1-166:13, 2024.
- Yanci Zhang & Han Yu, "LR-XFL: Logical Reasoning-based Explainable Federated Learning," in Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), pp. 21788-21796, 2024.
- Shanli Tan, Hao Cheng, Xiaohu Wu, Han Yu, Tiantian He, Yew Soon Ong, Chongjun Wang & Xiaofeng Tao, "FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants," in Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), pp. 15231-15239, 2024.
- Cong Su, Guoxian Yu, Jun Wang, Hui Li, Qingzhong Li & Han Yu, "Multi-dimensional Fair Federated Learning," in Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-24), pp. 15083-15090, 2024.
- Chang Liu, Peng Hou, Anxiang Zeng & Han Yu, "Transformer-empowered Multi-modal Item Embedding for Enhanced Image Search in E-Commerce," in Proceedings of the 36th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-24), pp. 22770-22778, 2024. (Innovative Application of AI Award)
- Hao Sun, Xiaoli Tang, Chengyi Yang, Zhenpeng Yu, Xiuli Wang, Qijie Ding, Zengxiang Li & Han Yu, "HiFi-Gas: Hierarchical Federated Learning Incentive Mechanism Enhanced Gas Usage Estimation," in Proceedings of the 36th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-24), pp. 22824-22832, 2024. (Innovative Application of AI Award)
- Yuliang Shi, Lin Cheng, Cheng Jiang, Hui Zhang, Guifeng Li, Xiaoli Tang, Han Yu, Zhiqi Shen & Cyril Leung, "IBCA: An Intelligent Platform for Social Insurance Benefit Qualification Status Assessment," in Proceedings of the 36th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-24), pp. 22815-22823, 2024. (Innovative Application of AI Award)
- Tianlin Li, Yue Cao, Jian Zhang, Shiqian Zhao, Yihao Huang, Aishan Liu, Qing Guo & Yang Liu, "RUNNER: Responsible UNfair NEuron Repair for Enhancing Deep Neural Network Fairness," in Proceedings the 46th IEEE/ACM International Conference on Software Engineering (ICSE'24), pp. 9:1-9:13, 2024.
- Yizhou Chen, Anxiang Zeng, Qingtao Yu, Kerui Zhang, Yuanpeng Cao, Kangle Wu, Guangda Huzhang, Han Yu & Zhiming Zhou, "Recurrent Temporal Revision Graph Networks," in Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS'23), pp. 69348-69360, 2023.
- Ming Hu, Zeke Xia, Dengke Yan, Zhihao Yue, Jun Xia, Yihao Huang, Yang Liu & Mingsong Chen, "GitFL: Uncertainty-Aware Real-Time Asynchronous Federated Learning using Version Control," in Proceedings the 2023 IEEE Real-Time Systems Symposium (RTSS'23), pp. 145-157, 2023.
- Yuqiang Sun, Zhengzi Xu, Chengwei Liu, Yiran Zhang & Yang Liu, "Who is the Real Hero? Measuring Developer Contribution via Multi-dimensional Data Integration," in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE'23), pp. 825-836, 2023.
- Liping Yi, Gang Wang, Xiaoguang Liu, Zhuan Shi & Han Yu, "FedGH: Heterogeneous Federated Learning with Generalized Global Header," in Proceedings of the 31st ACM Multimedia Conference (ACM MM'23), 2023.
- Xiaoli Tang & Han Yu, "Competitive-Cooperative Multi-Agent Reinforcement Learning for Auction-based Federated Learning," in Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), 2023. (KDDSG23 Best Poster Runner-Up Award)
- Yuanyuan Chen, Zichen Chen, Pengcheng Wu & Han Yu, "FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning," in Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), 2023.
- Tianlin Li, Zhiming Li, Anran Li, Mengnan Du, Aishan Liu, Qing Guo, Guozhu Meng & Yang Liu, "Fairness via Group Contribution Matching," in Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23), 2023.
- Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li & Yang Liu, "FAIRER: Fairness as Decision Rationale Alignment," in Proceedings of the 40th International Conference on Machine Learning (ICML'23), 2023.
- Jihu Wang, Yuliang Shi, Han Yu, Xinjun Wang, Zhongmin Yan & Fanyu Kong, "Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation," in Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'23), 2023.
- Han Liu, Sen Chen, Ruitao Feng, Chengwei Liu, Kaixuan Li, Zhengzi Xu, Liming Nie, Yang Liu & Yixiang Chen, "A Comprehensive Study on Quality Assurance Tools for Java," in Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA'23), 2023.
- Xiaoli Tang & Han Yu, "Utility-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning," in Proceedings of the 2023 IEEE International Conference on Multimedia and Expo (ICME'23), 2023.
- Yuxin Shi, Zelei Liu, Zhuan Shi & Han Yu, "Fairness-Aware Client Selection for Federated Learning," in Proceedings of the 2023 IEEE International Conference on Multimedia and Expo (ICME'23), 2023. (KDDSG23 Best Poster Award)
- Yulan Gao, Yansong Zhao & Han Yu, "Multi-Tier Client Selection for Mobile Federated Learning Networks," in Proceedings of the 2023 IEEE International Conference on Multimedia and Expo (ICME'23), 2023.
- Zhiwei Xiong, Han Yu & Zhiqi Shen, "Federated Learning-based Personalized Image Aesthetics Assessment," in Proceedings of the 2023 IEEE International Conference on Multimedia and Expo (ICME'23), 2023.
- Zhuan Shi, Zhenyu Yao, Liping Yi, Han Yu, Lan Zhang & Xiang-Yang Li, "FedWM: Federated Crowdsourcing Workforce Management Service for Productive Laziness," in Proceedings of the 2023 IEEE International Conference on Web Services (ICWS'23), 2023.
- Shipeng Wang, Qingzhong Li, Lizhen Cui, Yali Jiang, Zhiqi Shen & Han Yu, "CSP-RM: Reputation Management Decision Support for Crowdsourcing Service Providers," in Proceedings of the 2023 IEEE International Conference on Web Services (ICWS'23), 2023.
- Xavier Tan, Wei Yang Bryan Lim, Dusit Niyato & Han Yu, "Reputation-Aware Opportunistic Budget Optimization for Auction-based Federation Learning," in Proceedings of the 2023 International Joint Conference on Neural Networks (IJCNN'23), 2023.
- Anran Li, Hongyi Peng, Lan Zhang, Jiahui Huang, Qing Guo, Han Yu & Yang Liu, "FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning," in Proceedings of the 2023 IEEE International Conference on Computer Communications (INFOCOM'23), 2023.
- Yuekun Wang, Yuhang Ye, Yueming Wu, Weiwei Zhang, Yinxing Xue & Yang Liu, "Comparison and Evaluation of Clone Detection Techniques with Different Code Representations," in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE'23), 2023.
- Jiahui Wu, Zhengzi Xu, Wei Tang, Lyuye Zhang, Yueming Wu, Chengyue Liu , Kairan Sun, Lida Zhao & Yang Liu, "OSSFP: Precise and Scalable C/C++ Third-Party Library Detection using Fingerprinting Functions," in Proceedings of the 45th IEEE/ACM International Conference on Software Engineering (ICSE'23), 2023.
- Yizhou Chen, Guangda Huzhang, Qingtao Yu, Hui Sun, Heng-Yi Li, Jingyi Li, Yabo Ni, Anxiang Zeng, Han Yu & Zhiming Zhou, "Clustered Embedding Learning for Large-scale Recommender Systems," in Proceedings of the ACM Web Conference 2023 (WWW'23), 2023.
- Rakpong Kaewpuang, Minrui Xu, Dusit Niyato, Han Yu, Zehui Xiong & Sherman Shen, "Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning," in Proceedings of the 2023 International Conference on Computing, Networking and Communications (ICNC'23), pp. 71-76, 2023.
- Yuanyuan Chen, Zichen Chen, Sheng Guo, Yansong Zhao, Zelei Liu, Pengcheng Wu, Chengyi Yang, Zengxiang Li & Han Yu, "Efficient Training of Large-Scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout," in Proceedings of the 35th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-23), pp. 15485-15493, 2023. (Innovative Application of AI Award)
- Xu Guo, Boyang Li & Han Yu, "Improving the Sample Efficiency of Prompt Tuning with Domain Adaptation," in Findings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP'22), pp. 3523-3537, 2022.
- Minrui Xu, Wei Chong Ng, Dusit Niyato, Han Yu, Chunyan Miao, Dong In Kim & Sherman Shen, "Stochastic Resource Allocation in Quantum Key Distribution for Secure Federated Learning," in Proceedings of the 2022 IEEE Global Communications Conference (GLOBECOM'22), pp. 4377-4382, 2022.
- Yulan Gao, Ziqiang Ye, Han Yu, Zehui Xiong, Yue Xiao, Dusit Niyato, "Multi-Resource Allocation for On-Device Distributed Federated Learning Systems," in Proceedings of the 2022 IEEE Global Communications Conference (GLOBECOM'22), pp. 160-165, 2022.
- Liming Zhai, Qing Guo, Xiaofei Xie, Lei Ma, Yi Estelle Wang & Yang Liu, "A3GAN: Attribute-Aware Anonymization Networks for Face De-identification," in Proceedings of the 30th ACM Multimedia Conference (ACM MM'22), pp. 5303-5313, 2022.
- Lyuye Zhang, Chengwei Liu, Zhengzi Xu, Sen Chen, Lingling Fan & Bihuan Chen, "Has My Release Disobeyed Semantic Versioning? Static Detection Based On Semantic Differencing," in Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering (ASE'22), pp. 51:1-51:12, 2022. (Distinguished Paper Award)
- Jiawen Kang, Dongdong Ye, Jiangtian Nie, Jiang Xiao, Xianjun Deng, Siming Wang, Zehui Xiong, Rong Yu & Dusit Niyato, "Blockchain-based Federated Learning for Industrial Metaverse: Incentive Schemes with Optimal AoI," in Proceedings of the 5th IEEE International Conference on Blockchain (Blockchain'22), 2022. (Best Paper Award)
- Yanci Zhang & Han Yu, "Towards Verifiable Federated Learning," in Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI'22), 2022.
- Ruijun Gao, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Huazhu Fu, Wei Feng, Yang Liu & Song Wang, "Can You Spot the Chameleon? Adversarially Camouflaging Images from Co-Salient Object Detection," in Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'22), 2022.
- Xiaoguang Li, Qing Guo, Di Lin, Ping Li, Wei Feng & Song Wan, "MISF: Multi-level Interactive Siamese Filtering for High-Fidelity Image Inpainting," in Proceedings of the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'22), 2022.
- Shenglai Zeng, Zonghang Li, Hongfang Yu, Yihong He, Zenglin Xu, Dusit Niyato & Han Yu, "Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training," in Proceedings of the 27th International Conference on Database Systems for Advanced Applications (DASFAA-22), 2022.
- Yuanchao Loh, Zichen Chen, Yansong Zhao & Han Yu, "FLAS: A Platform for Studying Attacks on Federated Learning," in Proceedings of the 14th International Conference on Social Computing and Social Media (SCSM'22), 2022.
- Zelei Liu, Yuanyuan Chen, Yansong Zhao, Han Yu, Yang Liu, Renyi Bao, Jinpeng Jiang, Zaiqing Nie, Qian Xu & Qiang Yang, "Contribution-Aware Federated Learning for Smart Healthcare," in Proceedings of the 34th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-22), 2022. (Innovative Application of AI Award)
- Heng-Yi Li, Yabo Ni, Anxiang Zeng, Han Yu & Chunyan Miao, "Prior-Guided Transfer Learning for Enhancing Item Representation in E-commerce," in Proceedings of the 34th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-22), 2022. (Innovative Application of AI Award)
- Daifei Feng, Cicilia Helena, Wei Yang Bryan Lim, Jer Shyuan Ng, Hongchao Jiang, Zehui Xiong, Jiawen Kang, Han Yu, Dusit Niyato & Chunyan Miao, "CrowdFL: A Marketplace for Crowdsourced Federated Learning," in Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), 2022.
- Xuan Rong Zane Ho, Wei Yang Bryan Lim, Hongchao Jiang, Jer Shyuan Ng, Han Yu, Zehui Xiong, Dusit Niyato and Chunyan Miao, "Dynamic Incentive Mechanism Design for COVID-19 Social Distancing," in Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22), 2022.
- Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong, Sahil Garg, Yang Zhang, Dusit Niyato & Chunyan Miao, "Dynamic edge association in hierarchical federated learning networks," in Proceedings of the 20th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom'21), 2021. (Best Paper Award)
- Haizhi Yang, Tengyun Wang, Xiaoli Tang, Qianyu Li, Yueyue Shi, Siyu Jiang, Han Yu & Hengjie Song, "Multi-task Learning for Bias-Free Joint CTR Prediction and Market Price Modeling in Online Advertising," in Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM'21), 2021.
- Yihao Huang, Qing Guo , Felix Juefei-Xu, Lei Ma, Weikai Miao, Yang Liu & Geguang Pu, "AdvFilter: Predictive Perturbation-aware Filtering against Adversarial Attack via Multi-domain Learning," in Proceedings of the 29th ACM International Conference on Multimedia (ACM MM'21), 2021.
- Qing Guo, Xiaoguang Li, Felix Juefei-Xu, Hongkai Yu, Yang Liu & Song Wang, "JPGNet: Joint Predictive Filtering and Generative Network for Image Inpainting," in Proceedings of the 29th ACM International Conference on Multimedia (ACM MM'21), 2021.
- Pye Sone Kyaw & Han Yu, "Personalised Federated Learning: A Combinational Approach," in Proceedings of the 1st International Student Conference on Artificial Intelligence (STCAI'21), 2021. (Best Paper Award)
- Binyu Tian, Felix Juefei-Xu, Qing Guo, Xiaofei Xie, Xiaohong Li & Yang Liu, "AVA: Adversarial Vignetting Attack against Visual Recognition," in Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI'21), 2021.
- Xianshuai Cao, Yuliang Shi, Han Yu, Jihu Wang, Xinjun Wang, Zhongmin Yan & Zhiyong Chen, "DEKR: Description Enhanced Knowledge Graph for Machine Learning Method Recommendation," in Proceedings of the 44th ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'21), 2021.
- Shangqing Liu, Yu Chen, Xiaofei Xie, Jing Kai Siow & Yang Liu, "Retrieval-Augmented Generation for Code Summarization via Hybrid GNN," in Proceedings of the 9th International Conference on Learning Representation (ICLR'21), 2021.
- Qing Guo, Ziyi Cheng, Felix Juefei-Xu, Lei Ma, Xiaofei Xie, Yang Liu & Jianjun Zhao, "Learning to Adversarially Blur Visual Object Tracking," in Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision (ICCV'21), 2021.
- Chang Liu, Han Yu, Zhiqi Shen, Ian Dixon, Yingxue Yu, Zhanning Gao, Pan Wang, Peiran Ren, Xuansong Xie, Lizhen Cui & Chunyan Miao, "Enhancing Viewing Experience of Generated Visual Storylines for Promotional Videos," in Proceedings of the 2021 IEEE International Conference on Multimedia and Expo (ICME'21), 2021.
- Chang Liu, Han Yu, Boyang Li, Zhiqi Shen, Zhanning Gao, Peiran Ren, Xuansong Xie, Lizhen Cui & Chunyan Miao, "Noise-resistant Deep Metric Learning with Ranking-based Instance Selection," in Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'21), 2021. (PREMIA Best Student Paper Runners Up Award)
- Wei Gao, Shangwei Guo, Tianwei Zhang, Han Qin, Yonggang Wen & Yang Liu, "Privacy-preserving Collaborative Learning with Automatic Transformation Search," in Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'21), 2021.
- Lan Fu, Changqing Zhou, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Wei Feng, Yang Liu & Song Wang, "Auto-Exposure Fusion for Single-Image Shadow Removal," in Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR'21), 2021.
- Xiaofei Xie, Wenbo Guo, Lei Ma, Wei Le, Jian Wang, Lingjun Zhou, Yang Liu & Xinyu Xing, "RNNRepair: Automatic RNN Repair via Model-based Analysis," in Proceedings of the 38th International Conference on Machine Learning (ICML'21), 2021.
- Xu Guo, Boyang Li, Han Yu & Chunyan Miao, "Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection," in Proceedings of the 2021 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT'21), 2021. (PREMIA Best Presentation Award)