8 citations · 10 across the 7 of their papers we have counts for
5 papers · 1 filter
Federated Personalization of Early-Exit Networks
Boyi Liu, Zimu Zhou, Cheng Fang +1
Personalized Federated Learning (PFL) excels at tailoring client-specific models, which is particularly critical for decentralized and heterogeneous data environments, yet existing…
CrowdHMTware: A Cross-level Co-adaptation Middleware for Context-aware Mobile DL Deployment
Sicong Liu, Bin Guo, Shiyan Luo +7
There are many deep learning (DL) powered mobile and wearable applications today continuously and unobtrusively sensing the ambient surroundings to enhance all aspects of human liv…
AdaShadow: Responsive Test-time Model Adaptation in Non-stationary Mobile Environments
Cheng Fang, Sicong Liu, Zimu Zhou +4
On-device adapting to continual, unpredictable domain shifts is essential for mobile applications like autonomous driving and augmented reality to deliver seamless user experiences…
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…
Enabling Resource-efficient AIoT System with Cross-level Optimization: A survey
Sicong Liu, Bin Guo, Cheng Fang +4
The emerging field of artificial intelligence of things (AIoT, AI+IoT) is driven by the widespread use of intelligent infrastructures and the impressive success of deep learning (D…