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Yanling Qin - IEEE Xplore Author Profile
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Yanling Qin

Publications
3
Citations
0
Publications by Year
20242025
Co-Authors:
Show All Co-Authors (8)
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Yanling Qin

Affiliation

School of Intelligent Systems Engineering
Sun Yat-sen University
Guangzhou, China

Publication Topics

Biography

Yanling Qin received the BE degree from the School of Artificial Intelligence, Hebei University of Technology, Tianjin, China, in 2021. She is currently working toward the MS degree with the School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China. Her primary research interests include game theory and mechanism design.(Based on document published on 25 November 2024).
Publications
3
Citations
0
Publications by Year
20242025
Co-Authors:
Show All Co-Authors (8)
Author's Published Works

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Participation-Dependent Privacy Preservation in Cross-Silo Federated Learning

Yanling Qin;Xiangping Zheng;Qian Ma;Guocheng Liao;Xu Chen

IEEE Transactions on Services Computing
Year: 2025 | Volume: 18, Issue: 1 | Journal Article |
In cross-silo federated learning (FL), clients of common interest cooperatively train a global model without sharing local sensitive data, but they still face potential privacy leakage due to privacy threats from malicious attackers. Although some articles have proposed effective privacy-preserving mechanisms for FL (such as differential privacy (DP)), clients in cross-silo FL are usually differen...Show More

Participation-Dependent Privacy Preservation in Cross-Silo Federated Learning

Yanling Qin;Xiangping Zheng;Qian Ma;Guocheng Liao;Xu Chen

Year: 2025 | Volume: 18, Issue: 1 | Journal Article |

Joint Resource Trading and Task Scheduling in Edge-Cloud Computing Networks

Qian Ma;Yanling Qin;Chaohui Zhu;Lin Gao;Xu Chen

IEEE Transactions on Networking
Year: 2024 | Early Access Article |
Edge-cloud computing networks integrate dispersed computing resources of edges and clouds through networks, which improves resource utilization by flexibly scheduling tasks to suitable computing nodes. The performance of edge-cloud computing networks depends significantly on the amount of computing resources and the task scheduling scheme. In this work, we propose a novel computing resource tradin...Show More

Joint Resource Trading and Task Scheduling in Edge-Cloud Computing Networks

Qian Ma;Yanling Qin;Chaohui Zhu;Lin Gao;Xu Chen

Year: 2024 | Early Access Article |

Air quality prediction based on ICEEMDAN-SSA-LSTM

Yanling Qin;Hongyan Ma;Wei He

2024 36th Chinese Control and Decision Conference (CCDC)
Year: 2024 | Conference Paper |
To address the problem that the Air Quality Index (AQI) is difficult to predict, a prediction model based on Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), Sparrow Search Algorithm (SSA), and Long Short-Term Memory (LSTM) is proposed. First, the AQI sequence was decomposed by ICEEMDAN. Second, the initial learning rate, max training epoch and the number of ...Show More

Air quality prediction based on ICEEMDAN-SSA-LSTM

Yanling Qin;Hongyan Ma;Wei He

Year: 2024 | Conference Paper |

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