1 citations · 1 across the 10 of their papers we have counts for
12 papers
Joint Optimization of Memory and Computing Frequency for Energy-Efficient DNN Inference
Yunchu Han, Zhaojun Nan, Sheng Zhou +1
Deep neural network (DNN) inference on mobile devices often incurs high latency and energy consumption due to limited computing and memory resources. To enable energy-efficient DNN…
Joint Memory Frequency and Computing Frequency Scaling for Energy-efficient DNN Inference
Yunchu Han, Zhaojun Nan, Sheng Zhou +1
Deep neural networks (DNNs) have been widely applied in diverse applications, but the problems of high latency and energy overhead are inevitable on resource-constrained devices. T…
Mobility-Aware Asynchronous Federated Learning with Dynamic Sparsification
Jintao Yan, Tan Chen, Yuxuan Sun +3
Asynchronous Federated Learning (AFL) enables distributed model training across multiple mobile devices, allowing each device to independently update its local model without waitin…
Robust DNN Partitioning and Resource Allocation Under Uncertain Inference Time
Zhaojun Nan, Yunchu Han, Sheng Zhou +1
In edge intelligence systems, deep neural network (DNN) partitioning and data offloading can provide real-time task inference for resource-constrained mobile devices. However, the…
DVFS-Aware DNN Inference on GPUs: Latency Modeling and Performance Analysis
Yunchu Han, Zhaojun Nan, Sheng Zhou +1
The rapid development of deep neural networks (DNNs) is inherently accompanied by the problem of high computational costs. To tackle this challenge, dynamic voltage frequency scali…
DiffCP: Ultra-Low Bit Collaborative Perception via Diffusion Model
Ruiqing Mao, Haotian Wu, Yukuan Jia +5
Collaborative perception (CP) is emerging as a promising solution to the inherent limitations of stand-alone intelligence. However, current wireless communication systems are unabl…