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Quantum Federated Learning: A Comprehensive Survey
Dinh C. Nguyen, Md Raihan Uddin, Shaba Shaon +3
Quantum federated learning (QFL) is a combination of distributed quantum computing and federated machine learning, integrating the strengths of both to enable privacy-preserving de…
Deep Learning Advancements in Anomaly Detection: A Comprehensive Survey
Haoqi Huang, Ping Wang, Jianhua Pei +3
The rapid expansion of data from diverse sources has made anomaly detection (AD) increasingly essential for identifying unexpected observations that may signal system failures, sec…
Meta-Computing Enhanced Federated Learning in IIoT: Satisfaction-Aware Incentive Scheme via DRL-Based Stackelberg Game
Xiaohuan Li, Shaowen Qin, Xin Tang +5
The Industrial Internet of Things (IIoT) leverages Federated Learning (FL) for distributed model training while preserving data privacy, and meta-computing enhances FL by optimizin…
Secure Resource Allocation via Constrained Deep Reinforcement Learning
Jianfei Sun, Qiang Gao, Cong Wu +3
The proliferation of Internet of Things (IoT) devices and the advent of 6G technologies have introduced computationally intensive tasks that often surpass the processing capabiliti…
Empowering Large Language Models in Wireless Communication: A Novel Dataset and Fine-Tuning Framework
Yushen Lin, Ruichen Zhang, Wenqi Huang +4
In this work, we develop a specialized dataset aimed at enhancing the evaluation and fine-tuning of large language models (LLMs) specifically for wireless communication application…
Task Delay and Energy Consumption Minimization for Low-altitude MEC via Evolutionary Multi-objective Deep Reinforcement Learning
Geng Sun, Weilong Ma, Jiahui Li +4
The low-altitude economy (LAE), driven by unmanned aerial vehicles (UAVs) and other aircraft, has revolutionized fields such as transportation, agriculture, and environmental monit…