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Posts by Collection
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publications
Fed2A: Federated Learning Mechanism in Asynchronous and Adaptive Modes
Published in Electronics, 2022
Recommended citation: S Liu, Q Chen, and L You, "Fed2A: Federated Learning Mechanism in Asynchronous and Adaptive Modes", Electronics, 11(9):1393, Apr 2022, doi: 10.3390/electronics11091393. https://www.mdpi.com/2079-9292/11/9/1393
Adaptation and Learning to Learn (ALL): An Integrated Approach for Small-Sample Parking Occupancy Prediction
Published in Mathematics, 2022
Recommended citation: H Qu, S Liu, J Li, Y Zhou, and R Liu, "Adaptation and Learning to Learn (ALL): An Integrated Approach for Small-Sample Parking Occupancy Prediction", Mathematics, 10(12):2039, Jun 2022, doi: 10.3390//math10122039. https://www.mdpi.com/2227-7390/10/12/2039
A Triple-step Asynchronous Federated Learning Mechanism for Client Activation, Interaction Optimization, and Aggregation Enhancement
Published in IEEE Internet of Things Journal, 2022
Recommended citation: L. You, S. Liu, Y. Chang and C. Yuen, "A Triple-Step Asynchronous Federated Learning Mechanism for Client Activation, Interaction Optimization, and Aggregation Enhancement," IEEE Internet of Things Journal, vol. 9, no. 23, pp. 24199-24211, Dec 2022, doi: 10.1109/JIOT.2022.3188556. https://ieeexplore.ieee.org/abstract/document/9815310
Federated Architecture for Personal Mobility Service in Autonomous Transportation System
Published in COTA International Conference of Transportation Professionals, 2022
Recommended citation: J He, Z Deng, S Liu, L You, M Zhou, M Cai, and S Cheng, "Federated Architecture for Personal Mobility Service in Autonomous Transportation System",COTA International Conference of Transportation Professionals, Jul 2022: 23-33, doi: 10.1061/9780784484265.003. https://ascelibrary.org/doi/abs/10.1061/9780784484265.003
Improving Parking Occupancy Prediction in Poor Data Conditions Through Customization and Learning to Learn
Published in International Conference on Knowledge Science, Engineering and Management, 2022
Recommended citation: H Qu, S Liu, Z Guo, L You, and J Li, "Improving Parking Occupancy Prediction in Poor Data Conditions Through Customization and Learning to Learn", International Conference on Knowledge Science, Engineering and Management, 159-172, Jul 2022, doi: 10.1007/978-3-031-10983-6_13. https://link.springer.com/chapter/10.1007/978-3-031-10983-6_13
TWAFR-GRU: An Integrated Model for Real-Time Charging Station Occupancy Prediction
Published in IEEE International Conference on Ubiquitous Intelligence and Computing, 2022
Recommended citation: Q Chen, S Liu, H Qu, R Zhu, and L You, "TWAFR-GRU: An Integrated Model for Real-Time Charging Station Occupancy Prediction", IEEE International Conference on Ubiquitous Intelligence and Computing, 1611-1618, Dec 2022, doi: 10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00233. https://ieeexplore.ieee.org/document/10189531
AFMeta: Asynchronous Federated Meta-learning with Temporally Weighted Aggregation
Published in IEEE International Conference on Ubiquitous Intelligence and Computing, 2022
Recommended citation: S Liu, H Qu, Q Chen, W Jian, R Liu, and L You, "AFMeta: Asynchronous Federated Meta-learning with Temporally Weighted Aggregation", IEEE International Conference on Ubiquitous Intelligence and Computing, 641-648, Dec 2022, doi: 10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00100. https://ieeexplore.ieee.org/document/10189596
ICMFed: An Incremental and Cost-Efficient Mechanism of Federated Meta-Learning for Driver Distraction Detection
Published in Mathematics, 2023
Recommended citation: Z Guo, L You, S Liu, J He, and B Zuo, "ICMFed: An Incremental and Cost-Efficient Mechanism of Federated Meta-Learning for Driver Distraction Detection", Mathematics, 11(8):1867, Apr 2023, doi: 10.3390/math11081867. https://www.mdpi.com/2227-7390/11/8/1867
Federated and Asynchronized Learning for Autonomous and Intelligent Things
Published in IEEE Network, 2023
Recommended citation: L You, S Liu, B Zuo, C Yuen, D Niyato, and H Vincent Poor, "Federated and Asynchronized Learning for Autonomous and Intelligent Things", IEEE Network, vol. 38, no. 2, pp. 286-293, Mar 2024, doi: 10.1109/MNET.2023.3321519. https://ieeexplore.ieee.org/document/10274563
FedRSM: Representational-Similarity-Based Secured Model Uploading for Federated Learning
Published in IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 2023
Recommended citation: G Chen, S Liu, X Yang, T Wang, L You, and F Xia, "FedRSM: Representational-Similarity-Based Secured Model Uploading for Federated Learning", IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 189-196, Nov, 2023, doi: 10.1109/TrustCom60117.2023.00046. https://ieeexplore.ieee.org/abstract/document/10538768
FedRC: Representational Consistency Guided Model Uploading Mechanism for Asynchronous Federated Learning
Published in EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2023
Recommended citation: S Liu, L You, and Y Zhou, "FedRC: Representational Consistency Guided Model Uploading Mechanism for Asynchronous Federated Learning", EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 239-256, Jul 2024, doi: 10.1007/978-3-031-63989-0_12. https://link.springer.com/chapter/10.1007/978-3-031-63989-0_12
AiFed: An Adaptive and Integrated Mechanism for Asynchronous Federated Data Mining
Published in IEEE Transactions on Knowledge and Data Engineering, 2023
Recommended citation: L You, S Liu, T Wang, B Zuo, Y Chang, and C Yuen, "AiFed: An Adaptive and Integrated Mechanism for Asynchronous Federated Data Mining", IEEE Transactions on Knowledge and Data Engineering, vol. 36, no. 9, pp. 4411-4427, Sep 2024, doi: 10.1109/TKDE.2023.3332770. https://ieeexplore.ieee.org/document/10316646
AFM3D: An Asynchronous Federated Meta-learning Framework for Driver Distraction Detection
Published in IEEE Transactions on Intelligent Transportation Systems, 2024
Recommended citation: S Liu, L You, R Zhu, B Liu, R Liu, H Yu, and C Yuen, "AFM3D: An Asynchronous Federated Meta-learning Framework for Driver Distraction Detection", IEEE Transactions on Intelligent Transportation Systems, vol. 25, no. 8, pp. 9659-9674, Aug 2024, doi: 10.1109/TITS.2024.3357138. https://ieeexplore.ieee.org/document/10423999
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Traffic Big Data Technology
Undergraduate, Sun Yat-Sen University, School of Intelligent Systems Engineering, 2022
Served as a teaching assistent for Instructor Prof. Linlin You in 2021/22 Spring.
Network and Communication Principles
Undergraduate, Sun Yat-Sen University, School of Intelligent Systems Engineering, 2022
Served as a teaching assistent for Instructor Prof. Linlin You in 2022/23 Fall.
Traffic Information Engineering
Postgraduate, Sun Yat-Sen University, School of Intelligent Systems Engineering, 2022
Served as a teaching assistent for Instructor Prof. Linlin You in 2022/23 Spring.
Traffic Big Data Technology
Undergraduate, Sun Yat-Sen University, School of Intelligent Systems Engineering, 2022
Served as a teaching assistent for Instructor Prof. Linlin You in 2022/23 Spring.
Cybersecurity and Privacy Summer School
Postgraduate, KTH, 2024
Served as a teaching assistant for Examiner Prof. Panos Papadimitratom in 2024 Spring.
Advanced Networked Systems Security
Postgraduate, KTH, 2024
Served as a teaching assistant for Examiner Prof. Panos Papadimitratom in 2024 Fall.