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ORCIDHan Yu 0001
Person information
- affiliation: Nanyang Technological University, School of Computer Science and Engineering, Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly, Singapore
Other persons with the same name
- Han Yu — disambiguation page
- Han Yu 0002 — General Electric Global Research Center, Niskayuna, NY, USA (and 1 more)
- Han Yu 0003 — University of Central Florida, School of Computer Science, Orlando, FL, USA
- Han Yu 0004
![[0000-0002-0514-2089]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-0514-2089")
— Zhongnan University of Economics and Law, School of Information and Safety Engineering, Wuhan, China - Han Yu 0005 — Shanghai Jiao Tong University, China
- Han Yu 0007 — University at Buffalo, New York, USA
- Han Yu 0008 — Rice University, Department of Electrical and Computer Engineering, Houston, TX, USA
- Han Yu 0009 — Tsinghua University, Department of Computer Science and Technology, Beijing, China
- Han Yu 0010 — Chalmers University of Technology, Gothenburg, Sweden (and 1 more)
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2020 – today
- 2024
[j85]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 J. Autom. Sinica 11(3): 800-802 (2024)- [j84]Rakpong Kaewpuang, Minrui Xu, Wei Yang Bryan Lim, Dusit Niyato, Han Yu, Jiawen Kang, Xuemin Shen:
Cooperative Resource Management in Quantum Key Distribution (QKD) Networks for Semantic Communication. IEEE Internet Things J. 11(3): 4454-4469 (2024) - [j83]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 Things J. 11(4): 5578-5588 (2024) - [j82]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 Things J. 11(5): 8414-8426 (2024) - [j81]Xiaoli Tang, Han Yu:
Efficient Large-Scale Personalizable Bidding for Multiagent Auction-Based Federated Learning. IEEE Internet Things J. 11(15): 26518-26530 (2024) - [j80]Yuanlu Chen, Alysa Ziying Tan, Siwei Feng, Han Yu, Tao Deng, Libang Zhao, Feng Wu:
General Federated Class-Incremental Learning With Lightweight Generative Replay. IEEE Internet Things J. 11(20): 33927-33939 (2024) - [j79]Liping Yi, Xiaorong Shi, Nan Wang, Gang Wang, Xiaoguang Liu, Zhuan Shi, Han Yu:
pFedKT: Personalized federated learning with dual knowledge transfer. Knowl. Based Syst. 292: 111633 (2024) - [j78]Rui Liu, Yuanyuan Chen, Anran Li, Yi Ding, Han Yu, Cuntai Guan:
Aggregating intrinsic information to enhance BCI performance through federated learning. Neural Networks 172: 106100 (2024) - [j77]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 174: 106222 (2024) - [j76]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. Proc. ACM Manag. Data 2(3): 144 (2024) - [j75]Siwei Feng, Han Yu, Yuebing Zhu:
MMVFL: A Simple Vertical Federated Learning Framework for Multi-Class Multi-Participant Scenarios. Sensors 24(2): 619 (2024) - [j74]Xiaohu Wu, Han Yu:
MarS-FL: Enabling Competitors to Collaborate in Federated Learning. IEEE Trans. Big Data 10(6): 801-811 (2024) - [j73]Chen Chen, Lingjuan Lyu, Han Yu, Gang Chen:
Practical Attribute Reconstruction Attack Against Federated Learning. IEEE Trans. Big Data 10(6): 851-863 (2024) - [j72]Pengwei Xing, Songtao Lu, Lingfei Wu, Han Yu:
BiG-Fed: Bilevel Optimization Enhanced Graph-Aided Federated Learning. IEEE Trans. Big Data 10(6): 903-914 (2024) - [j71]Haoran Shi, Yonghui Xu, Yali Jiang, Han Yu, Lizhen Cui:
Efficient Asynchronous Multi-Participant Vertical Federated Learning. IEEE Trans. Big Data 10(6): 940-952 (2024) - [j70]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 Trans. Big Data 10(6): 953-964 (2024) - [j69]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 Trans. Intell. Transp. Syst. 25(8): 9659-9674 (2024) - [j68]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 Trans. Mob. Comput. 23(6): 7238-7255 (2024) - [j67]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 Trans. Mob. Comput. 23(12): 15196-15209 (2024) - [j66]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 Trans. Neural Networks Learn. Syst. 35(7): 8726-8746 (2024) - [j65]Yuxin Shi, Han Yu, Cyril Leung:
Towards Fairness-Aware Federated Learning. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11922-11938 (2024) - [c158]Cong Su, Guoxian Yu, Jun Wang, Hui Li, Qingzhong Li, Han Yu:
Multi-Dimensional Fair Federated Learning. AAAI 2024: 15083-15090 - [c157]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. AAAI 2024: 15231-15239 - [c156]Chang Liu, Peng Hou, Anxiang Zeng, Han Yu:
Transformer-Empowered Multi-Modal Item Embedding for Enhanced Image Search in E-commerce. AAAI 2024: 22770-22778 - [c155]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. AAAI 2024: 22815-22823 - [c154]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. AAAI 2024: 22824-22832 - [c153]Zhiwei Xiong, Yunfan Zhang, Zhiqi Shen, Peiran Ren, Han Yu:
Image Aesthetics Assessment Via Learnable Queries. ICASSP 2024: 2805-2809 - [c152]Yuxin Shi, Han Yu:
Fairness-Aware Job Scheduling for Multi-Job Federated Learning. ICASSP 2024: 6350-6354 - [c151]Zichao Deng, Han Yu:
Noise-Resistant Graph Neural Network for Node Classification. ICASSP 2024: 7560-7564 - [c150]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. ICC 2024: 1115-1120 - [c149]Yulan Gao, Zhaoxiang Hou, Chengyi Yang, Zengxiang Li, Han Yu, Xiaoxiao Li:
The Prospect of Enhancing Large-Scale Heterogeneous Federated Learning with Foundation Models. ICME 2024: 1-6 - [c148]Qianyu Li, Xiaoli Tang, Siyao Zhou, Han Yu, Hengjie Song, Lizhen Cui, Xiaoxiao Li:
FedRMS: Privacy-Preserving Federated Knowledge Graph Embedding Through Randomization. ICME 2024: 1-6 - [c147]Alysa Ziying Tan, Siwei Feng, Han Yu:
FL-Clip: Bridging Plasticity and Stability in Pre-Trained Federated Class-Incremental Learning Models. ICME 2024: 1-6 - [c146]Xiaoli Tang, Han Yu, Xiaoxiao Li:
Agent-Oriented Joint Decision Support for Data Owners in Auction-Based Federated Learning. ICME 2024: 1-6 - [c145]Zhiwei Xiong, Yunfan Zhang, Zhiqi Shen, Peiran Ren, Han Yu:
Multi-modal Learnable Queries for Image Aesthetics Assessment. ICME 2024: 1-6 - [c144]Hongyi Peng, Han Yu, Xiaoli Tang, Xiaoxiao Li:
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler. ICML 2024 - [c143]Pengwei Xing, Songtao Lu, Han Yu:
Federated Neuro-Symbolic Learning. ICML 2024 - [c142]Xianjie Guo, Kui Yu, Hao Wang, Lizhen Cui, Han Yu, Xiaoxiao Li:
Sample Quality Heterogeneity-aware Federated Causal Discovery through Adaptive Variable Space Selection. IJCAI 2024: 4071-4079 - [c141]Xiaoli Tang, Han Yu, Run Tang, Chao Ren, Anran Li, Xiaoxiao Li:
Dual Calibration-based Personalised Federated Learning. IJCAI 2024: 4982-4990 - [c140]Xiaoli Tang, Han Yu, Zengxiang Li, Xiaoxiao Li:
A Bias-Free Revenue-Maximizing Bidding Strategy for Data Consumers in Auction-based Federated Learning. IJCAI 2024: 4991-4999 - [c139]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. IJCAI 2024: 5371-5379 - [c138]Xiaoli Tang, Han Yu, Xiaoxiao Li, Sarit Kraus:
Intelligent Agents for Auction-based Federated Learning: A Survey. IJCAI 2024: 8253-8261 - [c137]Qianyu Li, Jiebin Chen, Xiaoli Tang, Han Yu, Hengjie Song:
Modeling Time Decay Effect in Temporal Knowledge Graphs via Multivariate Hawkes Process. IJCNN 2024: 1-8 - [c136]Xavier Tan, Han Yu:
Hire When You Need to: Gradual Participant Recruitment for Auction-Based Federated Learning. IJCNN 2024: 1-8 - [c135]Xiaoli Tang, Han Yu:
Multi-Session Multi-Objective Budget Optimization for Auction-based Federated Learning. IJCNN 2024: 1-8 - [c134]Yansong Zhao, Siyao Zhou, Yulan Gao, Han Yu:
A Fair Incentive Mechanism for Federated Auctioning Networks. IJCNN 2024: 1-8 - [c133]Jianfu Zhang, Qingtao Yu, Yizhou Chen, Guoliang Zhou, Yawen Liu, Yawei Sun, Chen Liang, Guangda Huzhang, Yabo Ni, Anxiang Zeng, Han Yu:
An E-Commerce Dataset Revealing Variations during Sales. SIGIR 2024: 1162-1171 - [c132]Irwin King, Guodong Long, Zenglin Xu, Han Yu:
FL@FM-TheWebConf'24: International Workshop on Federated Foundation Models for the Web. WWW (Companion Volume) 2024: 1546-1547 - [i97]Yuxin Shi, Han Yu:
Fairness-Aware Job Scheduling for Multi-Job Federated Learning. CoRR abs/2401.02740 (2024) - [i96]Minrui Xu, Dusit Niyato, Jiawen Kang, Zehui Xiong, Yuan Cao, Yulan Gao, Chao Ren, Han Yu:
Generative AI-enabled Quantum Computing Networks and Intelligent Resource Allocation. CoRR abs/2401.07120 (2024) - [i95]Liping Yi, Han Yu, Chao Ren, Heng Zhang, Gang Wang, Xiaoguang Liu, Xiaoxiao Li:
pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning. CoRR abs/2402.01350 (2024) - [i94]Yulan Gao, Chao Ren, Han Yu:
Fairness-Aware Multi-Server Federated Learning Task Delegation over Wireless Networks. CoRR abs/2403.09153 (2024) - [i93]Xiaoli Tang, Han Yu, Xiaoxiao Li, Sarit Kraus:
Intelligent Agents for Auction-based Federated Learning: A Survey. CoRR abs/2404.13244 (2024) - [i92]Chao Ren, Han Yu, Hongyi Peng, Xiaoli Tang, Anran Li, Yulan Gao, Alysa Ziying Tan, Bo Zhao, Xiaoxiao Li, Zengxiang Li, Qiang Yang:
Advances and Open Challenges in Federated Learning with Foundation Models. CoRR abs/2404.15381 (2024) - [i91]Liping Yi, Han Yu, Chao Ren, Heng Zhang, Gang Wang, Xiaoguang Liu, Xiaoxiao Li:
pFedAFM: Adaptive Feature Mixture for Batch-Level Personalization in Heterogeneous Federated Learning. CoRR abs/2404.17847 (2024) - [i90]Zhiwei Xiong, Yunfan Zhang, Zhiqi Shen, Peiran Ren, Han Yu:
Multi-modal Learnable Queries for Image Aesthetics Assessment. CoRR abs/2405.01326 (2024) - [i89]Xiaoli Tang, Han Yu, Xiaoxiao Li:
Agent-oriented Joint Decision Support for Data Owners in Auction-based Federated Learning. CoRR abs/2405.05991 (2024) - [i88]Hongyi Peng, Han Yu, Xiaoli Tang, Xiaoxiao Li:
FedCal: Achieving Local and Global Calibration in Federated Learning via Aggregated Parameterized Scaler. CoRR abs/2405.15458 (2024) - [i87]Liping Yi, Han Yu, Chao Ren, Gang Wang, Xiaoguang Liu, Xiaoxiao Li:
Federated Model Heterogeneous Matryoshka Representation Learning. CoRR abs/2406.00488 (2024) - [i86]Yulan Gao, Ziqiang Ye, Han Yu:
Cost-Efficient Computation Offloading in SAGIN: A Deep Reinforcement Learning and Perception-Aided Approach. CoRR abs/2407.05571 (2024) - [i85]Zhilong Li, Xiaohu Wu, Xiaoli Tang, Tiantian He, Yew-Soon Ong, Mengmeng Chen, Qiqi Liu, Qicheng Lao, Han Yu:
Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated Learning. CoRR abs/2410.07286 (2024) - [i84]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. CoRR abs/2410.19321 (2024) - [i83]Yifei Zhang, Hao Zhu, Aiwei Liu, Han Yu, Piotr Koniusz, Irwin King:
Less is More: Extreme Gradient Boost Rank-1 Adaption for Efficient Finetuning of LLMs. CoRR abs/2410.19694 (2024) - 2023
- [j64]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 Mag. 44(1): 4-15 (2023) - [j63]Xiaojie Guo, Shugen Wang, Hanqing Zhao, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Jianchao Lu, Yun Xiao, Bo Long, Han Yu, Lingfei Wu:
Intelligent online selling point extraction and generation for e-commerce recommendation. AI Mag. 44(1): 16-29 (2023) - [j62]Yanyan Zou, Xueying Zhang, Jing Zhou, Shiliang Diao, Jiajia Chen, Zhuoye Ding, Zhen He, Xueqi He, Yun Xiao, Bo Long, Mian Ma, Sulong Xu, Han Yu, Lingfei Wu:
Automatic product copywriting for e-commerce. AI Mag. 44(1): 41-53 (2023) - [j61]Chang Liu, Han Yu:
AI-Empowered Persuasive Video Generation: A Survey. ACM Comput. Surv. 55(13s): 285:1-285:31 (2023) - [j60]Chao Ren, Tianjing Wang, Han Yu, Yan Xu, Zhao Yang Dong:
EFedDSA: An Efficient Differential Privacy-Based Horizontal Federated Learning Approach for Smart Grid Dynamic Security Assessment. IEEE J. Emerg. Sel. Topics Circuits Syst. 13(3): 817-828 (2023) - [j59]Jihu Wang, Yuliang Shi, Han Yu, Kun Zhang, Xinjun Wang, Zhongmin Yan, Hui Li:
Temporal Density-aware Sequential Recommendation Networks with Contrastive Learning. Expert Syst. Appl. 211: 118563 (2023) - [j58]Jiehuang Zhang, Ying Shu, Han Yu:
Fairness in Design: A Framework for Facilitating Ethical Artificial Intelligence Designs. Int. J. Crowd Sci. 7(1): 32-39 (2023) - [j57]Jiehuang Zhang, Han Yu:
EID: Facilitating Explainable AI Design Discussions in Team-Based Settings. Int. J. Crowd Sci. 7(2): 47-54 (2023) - [j56]Lin Cheng, Yuliang Shi, Lin Li, Han Yu, Xinjun Wang, Zhongmin Yan:
KLECA: knowledge-level-evolution and category-aware personalized knowledge recommendation. Knowl. Inf. Syst. 65(3): 1045-1065 (2023) - [j55]Tengyun Wang, Haizhi Yang, Yang Liu, Han Yu, Hengjie Song:
A multimodal approach for improving market price estimation in online advertising. Knowl. Based Syst. 266: 110392 (2023) - [j54]Hongli Bian, Jie Tian, Jialiang Yu, Han Yu:
Bayesian Co-evolutionary Optimization based entropy search for high-dimensional many-objective optimization. Knowl. Based Syst. 274: 110630 (2023) - [j53]Jihu Wang, Yuliang Shi, Han Yu, Zhongmin Yan, Hui Li, Zhenjie Chen:
A novel KG-based recommendation model via relation-aware attentional GCN. Knowl. Based Syst. 275: 110702 (2023) - [j52]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 Netw. 37(1): 118-124 (2023) - [j51]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 164: 323-334 (2023) - [j50]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. Proc. ACM Manag. Data 1(3): 212:1-212:24 (2023) - [j49]Haizhi Yang, Tengyun Wang, Xiaoli Tang, Han Yu, Fei Liu, Hengjie Song:
Dynamically Optimizing Display Advertising Profits Under Diverse Budget Settings. IEEE Trans. Knowl. Data Eng. 35(1): 362-376 (2023) - [j48]Guangda Huzhang, Zhen-Jia Pang, Yongqing Gao, Yawen Liu, Weijie Shen, Wen-Ji Zhou, Qianying Lin, Qing Da, Anxiang Zeng, Han Yu, Yang Yu, Zhi-Hua Zhou:
AliExpress Learning-to-Rank: Maximizing Online Model Performance Without Going Online. IEEE Trans. Knowl. Data Eng. 35(2): 1214-1226 (2023) - [j47]Yuxin Zhang, Jindong Wang, Yiqiang Chen, Han Yu, Tao Qin:
Adaptive Memory Networks With Self-Supervised Learning for Unsupervised Anomaly Detection. IEEE Trans. Knowl. Data Eng. 35(12): 12068-12080 (2023) - [j46]Chang'an Yi, Haotian Chen, Yonghui Xu, Huanhuan Chen, Yong Liu, Haishu Tan, Yuguang Yan, Han Yu:
Multicomponent Adversarial Domain Adaptation: A General Framework. IEEE Trans. Neural Networks Learn. Syst. 34(10): 6824-6838 (2023) - [j45]Alysa Ziying Tan, Han Yu, Lizhen Cui, Qiang Yang:
Towards Personalized Federated Learning. IEEE Trans. Neural Networks Learn. Syst. 34(12): 9587-9603 (2023) - [j44]Rakpong Kaewpuang, Suttinee Sawadsitang, Dusit Niyato, Han Yu:
Evolutionary Carrier Selection for Shared Truck Delivery Services. IEEE Trans. Veh. Technol. 72(5): 6778-6782 (2023) - [j43]Yu Guo, Ryan Wen Liu, Yuxu Lu, Jiangtian Nie, Lingjuan Lyu, Zehui Xiong, Jiawen Kang, Han Yu, Dusit Niyato:
Haze Visibility Enhancement for Promoting Traffic Situational Awareness in Vision-Enabled Intelligent Transportation. IEEE Trans. Veh. Technol. 72(12): 15421-15435 (2023) - [c131]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. AAAI 2023: 15485-15493 - [c130]Zi Qin Liew, Hongyang Du, Wei Yang Bryan Lim, Zehui Xiong, Dusit Niyato, Han Yu:
Economics of Semantic Communication in Metaverse: An Auction Approach. CCNC 2023: 398-403 - [c129]Shaojun Chen, Xavier Tan, Wei Yang Bryan Lim, Zehui Xiong, Han Yu:
Privacy Budget-Aware Incentive Mechanism for Federated Learning in Intelligent Transportation Systems. ICC 2023: 3060-3065 - [c128]Rakpong Kaewpuang, Minrui Xu, Dusit Niyato, Han Yu, Zehui Xiong, Xuemin Sherman Shen:
Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning. ICNC 2023: 71-76 - [c127]Yuxin Shi, Zelei Liu, Zhuan Shi, Han Yu:
Fairness-Aware Client Selection for Federated Learning. ICME 2023: 324-329 - [c126]Xiaoli Tang, Han Yu:
Utility-Maximizing Bidding Strategy for Data Consumers in Auction-Based Federated Learning. ICME 2023: 330-335 - [c125]Zhiwei Xiong, Han Yu, Zhiqi Shen:
Federated Learning for Personalized Image Aesthetics Assessment. ICME 2023: 336-341 - [c124]Yulan Gao, Yansong Zhao, Han Yu:
Multi-Tier Client Selection for Mobile Federated Learning Networks. ICME 2023: 666-671 - [c123]Zhuan Shi, Zhenyu Yao, Liping Yi, Han Yu, Lan Zhang, Xiang-Yang Li:
FedWM: Federated Crowdsourcing Workforce Management Service for Productive Laziness. ICWS 2023: 152-160 - [c122]Shipeng Wang, Qingzhong Li, Lizhen Cui, Yali Jiang, Zhiqi Shen, Han Yu:
CSP-RM: Reputation Management Decision Support for Crowdsourcing Service Providers. ICWS 2023: 161-169 - [c121]Xiaoli Tang, Han Yu:
Competitive-Cooperative Multi-Agent Reinforcement Learning for Auction-based Federated Learning. IJCAI 2023: 4262-4270 - [c120]Xavier Tan, Wei Yang Bryan Lim, Dusit Niyato, Han Yu:
Reputation-Aware Opportunistic Budget Optimization for Auction-based Federation Learning. IJCNN 2023: 1-8 - [c119]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. INFOCOM 2023: 1-10 - [c118]Liping Yi, Gang Wang, Xiaoguang Liu, Zhuan Shi, Han Yu:
FedGH: Heterogeneous Federated Learning with Generalized Global Header. ACM Multimedia 2023: 8686-8696 - [c117]Yizhou Chen, Anxiang Zeng, Qingtao Yu, Kerui Zhang, Yuanpeng Cao, Kangle Wu, Guangda Huzhang, Han Yu, Zhiming Zhou:
Recurrent Temporal Revision Graph Networks. NeurIPS 2023 - [c116]Rakpong Kaewpuang, Minrui Xu, Dusit Niyato, Han Yu, Zehui Xiong, Jiawen Kang:
Stochastic Qubit Resource Allocation for Quantum Cloud Computing. NOMS 2023: 1-5 - [c115]Jihu Wang, Yuliang Shi, Han Yu, Xinjun Wang, Zhongmin Yan, Fanyu Kong:
Mixed-Curvature Manifolds Interaction Learning for Knowledge Graph-aware Recommendation. SIGIR 2023: 372-382 - [c114]Ziqiang Ye, Yulan Gao, Yue Xiao, Minrui Xu, Han Yu, Dusit Niyato:
Smart Healthcare with Hybrid Mobile Edge-Quantum Computing: Dynamic Computation Offloading for Latency Improvement. VTC Fall 2023: 1-5 - [c113]Yizhou Chen, Guangda Huzhang, Anxiang Zeng, Qingtao Yu, Hui Sun, Heng-Yi Li, Jingyi Li, Yabo Ni, Han Yu, Zhiming Zhou:
Clustered Embedding Learning for Recommender Systems. WWW 2023: 1074-1084 - [e5]Randy Goebel, Han Yu, Boi Faltings, Lixin Fan, Zehui Xiong:
Trustworthy Federated Learning - First International Workshop, FL 2022, Held in Conjunction with IJCAI 2022, Vienna, Austria, July 23, 2022, Revised Selected Papers. Lecture Notes in Computer Science 13448, Springer 2023, ISBN 978-3-031-28995-8 [contents] - [i82]Rakpong Kaewpuang, Suttinee Sawadsitang, Dusit Niyato, Han Yu:
Evolutionary Carrier Selection for Shared Truck Delivery Services. CoRR abs/2301.03635 (2023) - [i81]