91 citations · 189 across the 11 of their papers we have counts for
12 papers
AutoMCU: Feasibility-First MCU Neural Network Customization via LLM-based Multi-Agent Systems
Penglin Dai, Zijie Zhou, Xincao Xu +3
Deploying neural networks on microcontroller units (MCUs) is critical for edge intelligence but remains challenging due to tight memory, storage, and computation constraints. Exist…
FedCoE: Bridging Generalization and Personalization via Federated Coordinated Dual-level MoEs
Penglin Dai, Fulian Li, Xincao Xu +3
Federated Learning (FL) has emerged as a promising paradigm for privacy-preserving distributed learning. However, existing FL methods face a fundamental challenge. Traditional aver…
Pragmatic Heterogeneous Collaborative Perception via Generative Communication Mechanism
Junfei Zhou, Penglin Dai, Quanmin Wei +3
Multi-agent collaboration enhances the perception capabilities of individual agents through information sharing. However, in real-world applications, differences in sensors and mod…
CoPEFT: Fast Adaptation Framework for Multi-Agent Collaborative Perception with Parameter-Efficient Fine-Tuning
Quanmin Wei, Penglin Dai, Wei Li +2
Multi-agent collaborative perception is expected to significantly improve perception performance by overcoming the limitations of single-agent perception through exchanging complem…
Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks
Tong Bu, Wei Fang, Jianhao Ding +3
Spiking Neural Networks (SNNs) have gained great attraction due to their distinctive properties of low power consumption and fast inference on neuromorphic hardware. As the most ef…
Joint Task Offloading and Resource Optimization in NOMA-based Vehicular Edge Computing: A Game-Theoretic DRL Approach
Xincao Xu, Kai Liu, Penglin Dai +4
Vehicular edge computing (VEC) becomes a promising paradigm for the development of emerging intelligent transportation systems. Nevertheless, the limited resources and massive tran…
Cooperative Sensing and Uploading for Quality-Cost Tradeoff of Digital Twins in VEC
Kai Liu, Xincao Xu, Penglin Dai +1
Recent advances in sensing technologies, wireless communications, and computing paradigms drive the evolution of vehicles in becoming an intelligent and electronic consumer product…
Cooperative Sensing and Heterogeneous Information Fusion in VCPS: A Multi-agent Deep Reinforcement Learning Approach
Xincao Xu, Kai Liu, Penglin Dai +3
Cooperative sensing and heterogeneous information fusion are critical to realize vehicular cyber-physical systems (VCPSs). This paper makes the first attempt to quantitatively meas…
On Jointly Optimizing Partial Offloading and SFC Mapping: A Cooperative Dual-agent Deep Reinforcement Learning Approach
Xinhan Wang, Huanlai Xing, Fuhong Song +3
Multi-access edge computing (MEC) and network function virtualization (NFV) are promising technologies to support emerging IoT applications, especially those computation-intensive.…
Evolutionary Multi-Objective Reinforcement Learning Based Trajectory Control and Task Offloading in UAV-Assisted Mobile Edge Computing
Fuhong Song, Huanlai Xing, Xinhan Wang +4
This paper studies the trajectory control and task offloading (TCTO) problem in an unmanned aerial vehicle (UAV)-assisted mobile edge computing system, where a UAV flies along a pl…
RTFN: A Robust Temporal Feature Network for Time Series Classification
Zhiwen Xiao, Xin Xu, Huanlai Xing +3
Time series data usually contains local and global patterns. Most of the existing feature networks pay more attention to local features rather than the relationships among them. Th…
STDPG: A Spatio-Temporal Deterministic Policy Gradient Agent for Dynamic Routing in SDN
Juan Chen, Zhiwen Xiao, Huanlai Xing +3
Dynamic routing in software-defined networking (SDN) can be viewed as a centralized decision-making problem. Most of the existing deep reinforcement learning (DRL) agents can addre…