10 citations · 11 across the 6 of their papers we have counts for
5 papers · 1 filter
AdaScale: Dynamic Context-aware DNN Scaling via Automated Adaptation Loop on Mobile Devices
Yuzhan Wang, Sicong Liu, Bin Guo +6
Deep learning is reshaping mobile applications, with a growing trend of deploying deep neural networks (DNNs) directly to mobile and embedded devices to address real-time performan…
Deep Learning Inference on Heterogeneous Mobile Processors: Potentials and Pitfalls
Sicong Liu, Wentao Zhou, Zimu Zhou +5
There is a growing demand to deploy computation-intensive deep learning (DL) models on resource-constrained mobile devices for real-time intelligent applications. Equipped with a v…
AdaOper: Energy-efficient and Responsive Concurrent DNN Inference on Mobile Devices
Zheng Lin, Bin Guo, Sicong Liu +4
Deep neural network (DNN) has driven extensive applications in mobile technology. However, for long-running mobile apps like voice assistants or video applications on smartphones,…
The Future of Cognitive Strategy-enhanced Persuasive Dialogue Agents: New Perspectives and Trends
Mengqi Chen, Bin Guo, Hao Wang +6
Persuasion, as one of the crucial abilities in human communication, has garnered extensive attention from researchers within the field of intelligent dialogue systems. We humans te…
EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control
Xiaochen Li, Sicong Liu, Zimu Zhou +3
The rise of mobile devices with abundant sensory data and local computing capabilities has driven the trend of federated learning (FL) on these devices. And personalized FL (PFL) e…